26_linear_regression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# ICS 434: DATA SCIENCE FUNDAMENTALS\n",
    "\n",
    "## Linear Regression\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# !pip install statsmodels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# %load ../standard_import.txt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import axes3d\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.preprocessing import scale\n",
    "import sklearn.linear_model as skl_lm\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from mpl_toolkits.mplot3d import axes3d\n",
    "\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as smf\n",
    "import sklearn.linear_model as skl_lm\n",
    "from sklearn.preprocessing import scale\n",
    "from sklearn.metrics import mean_squared_error, r2_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Single Linear Regression\n",
    "\n",
    "-  Also known as simple linear regression\n",
    "\n",
    "- A simple method to predict a *quantitative* response $Y$ on the basis of a single predictor variable $X$\n",
    "\n",
    "- Assume an approximately linear relationship between $X$ and $Y$\n",
    "\n",
    "- Remember that the equation of a line is:\n",
    "\n",
    "$$\n",
    "    Y = \\beta_o + \\beta_1X\n",
    "$$\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Example: Advertising Data\n",
    "\n",
    "- Displays sales (in thousands of units) for some product as a function of advertising budgets (in thousands of dollars) for TV, radio, and newspaper.\n",
    "* Which medium, or combination of media, contribute to sales?\n",
    "* How accurately can we estimate the effect of each medium on sales?\n",
    "* Is there synergy between the advertising media?\n",
    "* Etc.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TV</th>\n",
       "      <th>radio</th>\n",
       "      <th>newspaper</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>230.1</td>\n",
       "      <td>37.8</td>\n",
       "      <td>69.2</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>44.5</td>\n",
       "      <td>39.3</td>\n",
       "      <td>45.1</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17.2</td>\n",
       "      <td>45.9</td>\n",
       "      <td>69.3</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>151.5</td>\n",
       "      <td>41.3</td>\n",
       "      <td>58.5</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>180.8</td>\n",
       "      <td>10.8</td>\n",
       "      <td>58.4</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      TV  radio  newspaper  sales\n",
       "0  230.1   37.8       69.2   22.1\n",
       "1   44.5   39.3       45.1   10.4\n",
       "2   17.2   45.9       69.3    9.3\n",
       "3  151.5   41.3       58.5   18.5\n",
       "4  180.8   10.8       58.4   12.9"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "advertising = pd.read_csv('data/Advertising.csv', usecols=[1, 2, 3, 4])\n",
    "advertising.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinregressResult(slope=0.0475366404330197, intercept=7.032593549127702, rvalue=0.7822244248616063, pvalue=1.4673897001948012e-42, stderr=0.0026906071877968703, intercept_stderr=0.4578429402734785)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import linregress\n",
    "\n",
    "linreg = linregress(advertising[\"TV\"], advertising[\"sales\"])\n",
    "linreg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Linear Regression\n",
    "\n",
    "* `linregress` returns the intercept $\\beta_0$ and the slope $\\beta_1$ of the linear relationship between sales and advertising budget for TV\n",
    "\n",
    "$$\n",
    "    sales \\approx \\beta_o + \\beta_1 \\times \\text{TV}\n",
    "$$\n",
    "\n",
    "* Together, $\\beta_0$ and $\\beta_1$ are known as the model parameters\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18.91675365738263\n"
     ]
    }
   ],
   "source": [
    "some_tv_advertising = 250\n",
    "some_sales_prediction = linreg.intercept + linreg.slope * some_tv_advertising\n",
    "\n",
    "print(some_sales_prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 6))\n",
    "\n",
    "some_tv_advertising = 250\n",
    "some_sales_prediction = linreg.intercept + linreg.slope * some_tv_advertising\n",
    "\n",
    "plt.scatter(advertising[\"TV\"], advertising[\"sales\"])\n",
    "plt.xlim(-10, 320)\n",
    "plt.ylim(0, 28)\n",
    "plt.vlines(some_tv_advertising, 0, some_sales_prediction, color='red')\n",
    "plt.hlines(some_sales_prediction, -10, some_tv_advertising, color='red')\n",
    "plt.scatter(some_tv_advertising, some_sales_prediction, s=100, color='red');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 6))\n",
    "\n",
    "x_axis = np.arange(0, 320, 10)\n",
    "y_line = linreg.intercept + linreg.slope * x_axis\n",
    "\n",
    "plt.scatter(advertising[\"TV\"], advertising[\"sales\"])\n",
    "plt.scatter(x_axis, y_line, color='red', s=100);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 6))\n",
    "\n",
    "x_axis = np.arange(0, 320)\n",
    "y_line = linreg.intercept + linreg.slope * x_axis\n",
    "\n",
    "plt.scatter(advertising[\"TV\"], advertising[\"sales\"])\n",
    "plt.plot(x_axis, y_line, color='red', linewidth=4, alpha=0.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### The Quality of the Regression\n",
    "\n",
    "```python\n",
    ">>> linregress(advertising[\"TV\"], advertising[\"sales\"])\n",
    "\n",
    "LinregressResult(slope=0.0475366404330197, intercept=7.032593549127702, rvalue=0.7822244248616063, pvalue=1.4673897001948012e-42, stderr=0.0026906071877968703, intercept_stderr=0.4578429402734785)\n",
    "```\n",
    "\n",
    "*  The correlation coefficient for the relationship between TV and sales is rather high\n",
    "   * TV advertising budget explains $R^2 = 0.61$ of the variance in the product's sales\n",
    "\n",
    "\n",
    "* Recall that the error is the differnece between the predicted value and the actual value\n",
    "\n",
    "* If  $\\hat{y}_i = \\beta_0 + \\beta_1 x_i$, then the error for $i^{th}$ data point is $e_i = \\hat{y}_i - y_i$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TV           230.1\n",
       "radio         37.8\n",
       "newspaper     69.2\n",
       "sales         22.1\n",
       "Name: 0, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "some_point = advertising.iloc[0]\n",
    "some_point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 6))\n",
    "\n",
    "x_axis = np.arange(0, 320)\n",
    "y_line = linreg.intercept + linreg.slope * x_axis\n",
    "plt.scatter(advertising[\"TV\"], advertising[\"sales\"], alpha=0.2)\n",
    "plt.plot(x_axis, y_line, color='black', linewidth=4, alpha=0.5)\n",
    "\n",
    "y_hat = linreg.intercept + linreg.slope * some_point[\"TV\"]\n",
    "plt.scatter(some_point[\"TV\"], some_point[\"sales\"], color='red', s=100)\n",
    "plt.vlines(some_point[\"TV\"], some_point[\"sales\"], y_hat, color='red');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 6))\n",
    "\n",
    "x_axis = np.arange(0, 320)\n",
    "y_line = linreg.intercept + linreg.slope * x_axis\n",
    "plt.scatter(advertising[\"TV\"], advertising[\"sales\"], alpha=0.2)\n",
    "plt.plot(x_axis, y_line, color='black', linewidth=4, alpha=0.5)\n",
    "\n",
    "for i in range(advertising.shape[0]):\n",
    "    y_hat = linreg.intercept + linreg.slope * advertising.iloc[i][\"TV\"]\n",
    "#     plt.scatter(advertising.iloc[i][\"TV\"], advertising.iloc[i][\"sales\"], color='red', s=100)\n",
    "    plt.vlines(advertising.iloc[i][\"TV\"], advertising.iloc[i][\"sales\"], y_hat, color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### The Residual Sum of Squares\n",
    "\n",
    "* We can quantify how well a line fits the data simply by assessing the total error \n",
    "* To avoid that error values cancel out, we compute the sum of square of the error\n",
    "* We call that the residual sum of squares (RSS)\n",
    "\n",
    "$$\n",
    "RSS = e_1^2 + e_2^2 + \\cdots + e_n^2\n",
    "$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Regression Coefficients: Minimizing the RSS\n",
    "\n",
    "* Naturally, we want the linear regression model that provides the smallest RSS\n",
    "\n",
    "* The line with the smallest RSS is the best model under the current assumption\n",
    "  * Model is linear\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Regression Coefficients : Minimizing the RSS -- Cont'd \n",
    "\n",
    "<center><img src=\"https://www.dropbox.com/scl/fi/o7hq1n743rff6i4viq3ao/RSS_Examples.png?rlkey=26zgonbkczp6x2tdf2c5xzwxt&dl=1\" alt=\"drawing\" style=\"width:1200px\"/>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 10))\n",
    "x_axis = np.arange(-10, 320)\n",
    "\n",
    "models = [(linreg.intercept, linreg.slope), (-2, 0.2), (20, 0), (20, -0.1)]\n",
    "\n",
    "for (m, model) in enumerate(models):\n",
    "    plt.subplot(2, 2, m+1)\n",
    "    y_line = model[0] + model[1] * x_axis\n",
    "    plt.scatter(advertising[\"TV\"], advertising[\"sales\"], alpha=0.2)\n",
    "    RSS = 0 \n",
    "    for i in range(advertising.shape[0]):\n",
    "        y_hat = model[0] + model[1] * advertising.iloc[i][\"TV\"]\n",
    "        plt.vlines(advertising.iloc[i][\"TV\"], advertising.iloc[i][\"sales\"], y_hat, color='red')    \n",
    "        RSS += (y_hat - advertising.iloc[i][\"sales\"])**2\n",
    "    plt.plot(x_axis, y_line)\n",
    "    plt.title(\"RSS={}\".format(round(RSS, 1)), fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<center><img src=\"https://www.dropbox.com/scl/fi/6r98givlv8jtc7b68libz/curve.png?rlkey=89r9wri2ldou0mjbqaucy85kq&dl=1\" alt=\"drawing\" style=\"width:1000px\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Computing the RSS\n",
    "\n",
    "* For linear regression, we can use calculus to arrive at the closed form solutions of $\\beta_0$ and $\\beta_1$ that minimize the RSS\n",
    "\n",
    "* Minimize equation by finding where partial derivatives are equal to 0 \n",
    "\n",
    "$\n",
    "\\hspace{2in} \\beta_1 = \\frac{\\sum_{i=1}^{n} (x_i -\\bar{x})(y_i -\\bar{y})}{\\sum_{i=1}^{n} (x_i -\\bar{x})^2}\n",
    "$\n",
    "\n",
    "$\n",
    "\\hspace{2in} \\beta_0 = \\bar{y} - \\beta_1\\bar{x}\n",
    "$\n",
    "\n",
    "* For other ML models, we may resort to optimization algorithms to find the best parameters\n",
    "  * E.g.: gradient descent, genetic algorithms, particle swarm optimization, etc.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Question\n",
    "\n",
    "* Our data are samples from a larger population and getting new data may lead to different parameter estimates\n",
    "* How confident are we in our model estimates?\n",
    "* How can we quantify our belief in our parameter estimates?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Cofidence Interval of Model Parameters\n",
    "\n",
    "* One way we have done this in the past is using bootstrap\n",
    "  * Subsample with replacement the same number of points\n",
    "  * Compute the linear regression using the bootstrap sample\n",
    "  * Compute the 95% confidence interval of the model\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(200, 4)\n"
     ]
    }
   ],
   "source": [
    "print(advertising.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TV</th>\n",
       "      <th>radio</th>\n",
       "      <th>newspaper</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>4.1</td>\n",
       "      <td>11.6</td>\n",
       "      <td>5.7</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>243.2</td>\n",
       "      <td>49.0</td>\n",
       "      <td>44.3</td>\n",
       "      <td>25.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>171.3</td>\n",
       "      <td>39.7</td>\n",
       "      <td>37.7</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>57.5</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.5</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>43.0</td>\n",
       "      <td>25.9</td>\n",
       "      <td>20.5</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        TV  radio  newspaper  sales\n",
       "155    4.1   11.6        5.7    3.2\n",
       "147  243.2   49.0       44.3   25.4\n",
       "153  171.3   39.7       37.7   19.0\n",
       "6     57.5   32.8       23.5   11.8\n",
       "138   43.0   25.9       20.5    9.6"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# bootstrapping the data (same sample size)\n",
    "advertising.sample(advertising.shape[0], replace=True).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TV</th>\n",
       "      <th>radio</th>\n",
       "      <th>newspaper</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>38.0</td>\n",
       "      <td>40.3</td>\n",
       "      <td>11.9</td>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>25.1</td>\n",
       "      <td>25.7</td>\n",
       "      <td>43.3</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>210.7</td>\n",
       "      <td>29.5</td>\n",
       "      <td>9.3</td>\n",
       "      <td>18.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>216.8</td>\n",
       "      <td>43.9</td>\n",
       "      <td>27.2</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>237.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        TV  radio  newspaper  sales\n",
       "148   38.0   40.3       11.9   10.9\n",
       "44    25.1   25.7       43.3    8.5\n",
       "59   210.7   29.5        9.3   18.4\n",
       "69   216.8   43.9       27.2   22.3\n",
       "21   237.4    5.1       23.5   12.5"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "advertising.sample(advertising.shape[0], replace=True).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 first intercepts:\n",
      "[6.821, 7.278, 7.789, 6.747, 6.766, 7.058, 7.704, 7.063, 7.081, 7.056]\n",
      "10 first slopes:\n",
      "[0.05, 0.045, 0.041, 0.049, 0.049, 0.049, 0.045, 0.048, 0.048, 0.047]\n"
     ]
    }
   ],
   "source": [
    "bootstrap_intercepts = []\n",
    "bootstrap_slopes = []\n",
    "\n",
    "for i in range(50_000):\n",
    "    sample_indexes = np.random.choice(advertising.index, size=len(advertising.index))\n",
    "    bootstrap_sample = advertising.iloc[sample_indexes]\n",
    "    lr = linregress(bootstrap_sample[\"TV\"], bootstrap_sample[\"sales\"])    \n",
    "    bootstrap_intercepts.append(round(lr.intercept, 3))\n",
    "    bootstrap_slopes.append(round(lr.slope, 3))\n",
    "\n",
    "print(\"10 first intercepts:\")    \n",
    "print(bootstrap_intercepts[:10])\n",
    "print(\"10 first slopes:\")    \n",
    "print(bootstrap_slopes[:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 6))\n",
    "\n",
    "plt.scatter(advertising[\"TV\"], advertising[\"sales\"], alpha=0.3)\n",
    "\n",
    "x_axis = np.arange(-10, 320)\n",
    "\n",
    "for i in np.random.choice(range(50000), 1000, replace=False):\n",
    "    y_hat = bootstrap_intercepts[i] + bootstrap_slopes[i] * x_axis\n",
    "    plt.plot(x_axis, y_hat, color='red', alpha=0.02)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.403 7.697]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 5))\n",
    "\n",
    "plt.hist(bootstrap_intercepts, edgecolor='black', linewidth=1.2)\n",
    "plt.title(\"Distribution of Intercepts\")\n",
    "\n",
    "conf_interval = np.percentile(bootstrap_intercepts, [2.5, 97.5])\n",
    "print(conf_interval)\n",
    "\n",
    "plt.axvline(conf_interval[0], color=\"red\")\n",
    "plt.axvline(conf_interval[1], color=\"red\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.042 0.053]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 5))\n",
    "\n",
    "plt.hist(bootstrap_slopes, edgecolor='black', linewidth=1.2)\n",
    "plt.title(\"Distribution of Slopes\")\n",
    "\n",
    "conf_interval = np.percentile(bootstrap_slopes, [2.5, 97.5])\n",
    "print(conf_interval)\n",
    "\n",
    "plt.axvline(conf_interval[0], color=\"red\")\n",
    "plt.axvline(conf_interval[1], color=\"red\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Stats Model\n",
    "\n",
    "* This information can be found using the `Statsmodels` package\n",
    "  * We use ordinary least squares model to build the regression model\n",
    "  * Ordinary least squares (OLS) is a method for estimating the unknown parameters in a linear regression model\n",
    "  \n",
    "* Used the statistical language $R$'s notation to describe the model\n",
    "  * Here \"~\" can be interpreted as \"a function of\" or \"depends on\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinregressResult(slope=0.0475366404330197, intercept=7.032593549127702, rvalue=0.7822244248616063, pvalue=1.4673897001948012e-42, stderr=0.0026906071877968703, intercept_stderr=0.4578429402734785)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linregress(advertising[\"TV\"], advertising[\"sales\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    7.0326</td> <td>    0.458</td> <td>   15.360</td> <td> 0.000</td> <td>    6.130</td> <td>    7.935</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TV</th>        <td>    0.0475</td> <td>    0.003</td> <td>   17.668</td> <td> 0.000</td> <td>    0.042</td> <td>    0.053</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lcccccc}\n",
       "\\toprule\n",
       "                   & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{Intercept} &       7.0326  &        0.458     &    15.360  &         0.000        &        6.130    &        7.935     \\\\\n",
       "\\textbf{TV}        &       0.0475  &        0.003     &    17.668  &         0.000        &        0.042    &        0.053     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\end{center}"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.table.SimpleTable'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import statsmodels.formula.api as smf\n",
    "\n",
    "est = smf.ols('sales ~ TV', advertising).fit()\n",
    "est.summary().tables[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Intercept    7.032594\n",
       "TV           0.047537\n",
       "dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "est.params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      17.970775\n",
       "1       9.147974\n",
       "2       7.850224\n",
       "3      14.234395\n",
       "4      15.627218\n",
       "         ...    \n",
       "195     8.848493\n",
       "196    11.510545\n",
       "197    15.446579\n",
       "198    20.513985\n",
       "199    18.065848\n",
       "Length: 200, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# compute predicted values given the estimated model parameters\n",
    "\n",
    "est.predict(advertising[\"TV\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Interpreting the Simple Linear Regression\n",
    "\n",
    "$\\beta_0 = 7.0326$\n",
    "\n",
    "* The intercept is the expected mean value of $y$ when $x=0$\n",
    "  * If we spend $0 TV advertising, then we should expect, on average,  sales of 7.03 thousand units  \n",
    "\n",
    "* The intercept has no intrinsic meaning when $x$ never equals 0\n",
    "    \n",
    "$\\beta_1 = 0.0475$\n",
    "\n",
    "*  $\\beta_1$ quantifies the association between that variable and the response\n",
    "  * The **average** effect on the reponse ($y$) of a one unit increase in $x$\n",
    "* Each $1,000 spent on TV advertising  is associated with an increase in sales of approximately 47.5 additional units"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "from statsmodels.stats.outliers_influence import summary_table\n",
    "\n",
    "st, data, ss2 = summary_table(est, alpha=0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "   <th>Obs</th>    <th>Dep Var</th>       <th>Predicted</th>          <th>Std Error</th>            <th>Mean ci</th>            <th>Mean ci</th>          <th>Predict ci</th>         <th>Predict ci</th>           <th>Residual</th>             <th>Std Error</th>            <th>Student</th>                <th>Cook's</th>        \n",
       "</tr>\n",
       "<tr>\n",
       "    <th></th>    <th>Population</th>        <th>Value</th>          <th>Mean Predict</th>           <th>95% low</th>            <th>95% upp</th>            <th>95% low</th>            <th>95% upp</th>                <th></th>                 <th>Residual</th>            <th>Residual</th>                   <th>D</th>          \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>1.0</td>     <td>22.1</td>    <td>17.970774512765544</td> <td>0.32099116790047916</td> <td>17.337774319435486</td> <td>18.603774706095603</td> <td>11.513545889691956</td> <td>24.428003135839134</td>   <td>4.129225487234457</td>   <td>3.2428083506547387</td>  <td>1.2733486042740534</td>     <td>0.00794343302166503</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>2.0</td>     <td>10.4</td>     <td>9.147974048397074</td> <td>0.35946612171373415</td>  <td>8.439100573688425</td>  <td>9.856847523105724</td> <td>2.6828666363713127</td> <td>15.613081460422837</td>   <td>1.252025951602926</td>   <td>3.2387691236465606</td>  <td>0.38657462258169806</td>   <td>0.0009204339664699191</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>3.0</td>      <td>9.3</td>     <td>7.850223764575635</td> <td>0.4185011793359016</td>   <td>7.02493212443114</td>   <td>8.67551540472013</td>  <td>1.3713181056562735</td> <td>14.329129423494997</td>  <td>1.4497762354243653</td>    <td>3.231671098958042</td>  <td>0.4486150326039686</td>    <td>0.0016875502454444286</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>4.0</td>     <td>18.5</td>     <td>14.23439457473019</td> <td>0.23073371631706893</td> <td>13.779383653427363</td> <td>14.689405496033018</td>  <td>7.792178559693922</td> <td>20.676610589766458</td>  <td>4.2656054252698095</td>    <td>3.250477392799515</td>  <td>1.3123012129599836</td>    <td>0.004338752604050602</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>5.0</td>     <td>12.9</td>     <td>15.62721813941767</td> <td>0.24767713560076052</td> <td>15.138794499153134</td> <td>16.115641779682203</td>  <td>9.182556014972805</td> <td>22.071880263862532</td>  <td>-2.727218139417669</td>    <td>3.249230272764124</td>  <td>-0.8393428321402476</td>   <td>0.002046725626794406</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>6.0</td>      <td>7.2</td>     <td>7.446162320894968</td> <td>0.43777379903907726</td>  <td>6.582864737852164</td>  <td>8.309459903937771</td> <td>0.9623058324482594</td> <td>13.930018809341675</td> <td>-0.24616232089496748</td>   <td>3.229116818856375</td> <td>-0.07623208905218498</td>   <td>5.340447673606104e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>7.0</td>     <td>11.8</td>     <td>9.765950374026332</td> <td>0.33337431369247794</td>  <td>9.108530400763886</td> <td>10.423370347288778</td> <td>3.3062821730171406</td> <td>16.225618575035522</td>   <td>2.034049625973669</td>   <td>3.2415587139393742</td>  <td>0.6274912181065344</td>    <td>0.002082292779658906</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>8.0</td>     <td>13.2</td>     <td>12.74649772917667</td> <td>0.24147528648095948</td> <td>12.270304243771271</td>  <td>13.22269121458207</td>  <td>6.302750955642853</td> <td>19.190244502710488</td>  <td>0.4535022708233285</td>    <td>3.249697065107017</td>  <td>0.13955216801366502</td>  <td>5.3765390400867915e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <td>9.0</td>      <td>4.8</td>    <td>7.4414086568516655</td> <td>0.43800259582072804</td>  <td>6.577659882556574</td>  <td>8.305157431146757</td> <td>0.9574920788117227</td>  <td>13.92532523489161</td>  <td>-2.6414086568516657</td>  <td>3.2290857924497027</td>  <td>-0.8180051031867432</td>   <td>0.006155682784170733</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>10.0</td>     <td>10.6</td>    <td>16.530414307645046</td> <td>0.2706361514056093</td>  <td>15.996715086939483</td> <td>17.064113528350607</td> <td>10.082162831154179</td> <td>22.978665784135913</td>  <td>-5.930414307645046</td>    <td>3.247398559231463</td>  <td>-1.8262046371815082</td>   <td>0.011581620158297331</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>11.0</td>      <td>8.6</td>    <td>10.174765481750303</td> <td>0.31705564656532703</td>  <td>9.549526205277552</td> <td>10.800004758223054</td>  <td>3.718293039407727</td>  <td>16.63123792409288</td>  <td>-1.574765481750303</td>   <td>3.2431954991839858</td>  <td>-0.4855598381739635</td>   <td>0.0011266272392702998</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>12.0</td>     <td>17.4</td>     <td>17.23871025009704</td> <td>0.2936540129804136</td>   <td>16.6596194040636</td>  <td>17.817801096130477</td> <td>10.786543292101868</td>  <td>23.69087720809221</td>  <td>0.1612897499029593</td>   <td>3.2453980725955205</td> <td>0.049697986593665276</td>  <td>1.0110753583244568e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>13.0</td>      <td>9.2</td>     <td>8.163965591433566</td> <td>0.4037955927680105</td>   <td>7.367673625022752</td>  <td>8.96025755784438</td>   <td>1.688690065121552</td>  <td>14.63924111774558</td>   <td>1.036034408566433</td>    <td>3.23354147154592</td>   <td>0.32040238781014196</td>   <td>0.0008004381338116445</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>14.0</td>      <td>9.7</td>    <td>11.667415991347122</td> <td>0.2662009362211627</td>  <td>11.142463092503244</td>   <td>12.192368890191</td>   <td>5.219882525603069</td> <td>18.114949457091175</td>  <td>-1.9674159913471225</td>   <td>3.247765137829581</td>  <td>-0.6057753279111521</td>   <td>0.0012326594024323152</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>15.0</td>     <td>19.0</td>     <td>16.73482186150703</td> <td>0.2768797358793503</td>   <td>16.18881018309492</td>  <td>17.28083353991914</td> <td>10.285539653474313</td> <td>23.184104069539746</td>  <td>2.2651781384929706</td>    <td>3.246872178082408</td>  <td>0.6976493111689962</td>    <td>0.0017696863630991143</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>16.0</td>     <td>22.4</td>     <td>16.32125308973976</td> <td>0.2646187608915433</td>  <td>15.799420268298887</td>  <td>16.84308591118063</td>  <td>9.873972908188946</td> <td>22.768533271290572</td>   <td>6.078746910260239</td>   <td>3.2478944318327905</td>   <td>1.871596210357735</td>    <td>0.011626038913078581</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>17.0</td>     <td>12.5</td>    <td>10.255577770486436</td> <td>0.3139313593819662</td>   <td>9.636499642945045</td> <td>10.874655898027827</td>  <td>3.799699056176115</td> <td>16.711456484796756</td>   <td>2.244422229513564</td>    <td>3.243499411213576</td>  <td>0.6919755316600471</td>    <td>0.002242813878073586</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>18.0</td>     <td>24.4</td>    <td>20.409404166979456</td> <td>0.4286943085577553</td>  <td>19.564011497855645</td> <td>21.254796836103267</td>  <td>13.92790734827367</td> <td>26.890900985685242</td>   <td>3.990595833020542</td>    <td>3.230334737880334</td>  <td>1.2353505617312812</td>    <td>0.013438500709651345</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>19.0</td>     <td>11.3</td>    <td>10.322129067092664</td> <td>0.3113853304886954</td>   <td>9.708071753027873</td> <td>10.936186381157455</td> <td>3.8667298826237904</td> <td>16.777528251561538</td>  <td>0.9778709329073365</td>    <td>3.243744827341181</td>  <td>0.30146358143370783</td>  <td>0.00041873826137191417</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>20.0</td>     <td>14.6</td>    <td>14.034740684911508</td> <td>0.23042284318185957</td> <td>13.580342810864702</td> <td>14.489138558958315</td> <td>7.5925679401131205</td> <td>20.476913429709896</td>  <td>0.5652593150884915</td>    <td>3.250499445052438</td>  <td>0.17389921907197017</td>   <td>7.598294766503545e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>21.0</td>     <td>18.0</td>    <td>17.414595819699212</td> <td>0.29992713713924213</td> <td>16.823134263183942</td> <td>18.006057376214482</td> <td>10.961306811858297</td> <td>23.867884827540127</td>  <td>0.5854041803007881</td>    <td>3.244824346764194</td>  <td>0.18041167032186667</td>  <td>0.00013904276624749297</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>22.0</td>     <td>12.5</td>    <td>18.317791987926586</td> <td>0.3349624727729092</td>   <td>17.65724013719995</td> <td>18.978343838653224</td> <td>11.857804294951984</td>  <td>24.77777968090119</td>  <td>-5.8177919879265865</td>   <td>3.241394988393127</td>  <td>-1.7948420383072998</td>    <td>0.01720088789738924</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>23.0</td>      <td>5.6</td>     <td>7.660077202843556</td> <td>0.4275264753161854</td>   <td>6.816987521283317</td>  <td>8.503166884403795</td> <td>1.1788803645243968</td> <td>14.141274041162717</td>  <td>-2.0600772028435568</td>  <td>3.2304895049899076</td>  <td>-0.6376981567844445</td>   <td>0.0035611452472006605</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>24.0</td>     <td>15.5</td>    <td>17.885208559986108</td> <td>0.3176384170705466</td>  <td>17.258820049891497</td> <td>18.511597070080718</td> <td>11.428624725521981</td> <td>24.341792394450234</td>  <td>-2.3852085599861077</td>  <td>3.2431384745254306</td>  <td>-0.7354630641650711</td>   <td>0.0025943394475503477</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>25.0</td>      <td>9.7</td>     <td>9.994126248104827</td>  <td>0.324163863230972</td>   <td>9.354869444131193</td> <td>10.633383052078461</td>  <td>3.536281289659981</td> <td>16.451971206549672</td>  <td>-0.2941262481048277</td>   <td>3.242492732254213</td> <td>-0.09070991745919757</td>   <td>4.111977447400488e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>26.0</td>     <td>12.0</td>     <td>19.52997631896859</td> <td>0.38764409327620025</td>  <td>18.76553539184885</td>  <td>20.29441724608833</td>  <td>13.05854045225859</td>  <td>26.00141218567859</td>   <td>-7.52997631896859</td>   <td>3.2355174834783837</td>  <td>-2.327286549190083</td>    <td>0.038873045173275146</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>27.0</td>     <td>15.0</td>     <td>13.82557946700622</td> <td>0.23069121439746448</td> <td>13.370652360231693</td> <td>14.280506573780746</td>  <td>7.383369371211208</td> <td>20.267789562801234</td>  <td>1.1744205329937802</td>    <td>3.250480409500424</td>  <td>0.3613067562447732</td>    <td>0.0003287677234890113</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>28.0</td>     <td>15.9</td>     <td>18.44614091709574</td> <td>0.34027186356043454</td> <td>17.775118854939453</td> <td>19.117162979252026</td> <td>11.985074220815209</td> <td>24.907207613376272</td>  <td>-2.546140917095739</td>   <td>3.2408419257679526</td>  <td>-0.7856418101886915</td>   <td>0.003402166482447813</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>29.0</td>     <td>18.9</td>    <td>18.859709688863013</td> <td>0.35784755909653243</td> <td>18.154028047924452</td> <td>19.565391329801574</td> <td>12.394951470318205</td> <td>25.324467907407822</td> <td>0.040290311136985224</td>  <td>3.2389483560864125</td> <td>0.012439318787307736</td>   <td>9.443897647389483e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>30.0</td>     <td>10.5</td>     <td>10.38868036369889</td> <td>0.30886425497699127</td>  <td>9.779594654606118</td> <td>10.997766072791663</td>  <td>3.93375219625148</td>   <td>16.8436085311463</td>   <td>0.11131963630110953</td>  <td>3.2439858509160806</td>  <td>0.03431569723698812</td>   <td>5.337440623893835e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>31.0</td>     <td>21.4</td>    <td>20.956075531959183</td> <td>0.4550906188776845</td>  <td>20.058628877534144</td>  <td>21.85352218638422</td> <td>14.467583970477143</td> <td>27.444567093441222</td>  <td>0.44392446804081587</td>  <td>3.2267218438464367</td>  <td>0.1375775444937741</td>   <td>0.00018825122895388218</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>32.0</td>     <td>11.9</td>    <td>12.399480254015627</td> <td>0.24805888698623182</td> <td>11.910303793346754</td>  <td>12.8886567146845</td>   <td>5.95476103161676</td>  <td>18.844199476414495</td> <td>-0.49948025401562646</td>  <td>3.2492011506727887</td> <td>-0.15372401733644675</td>   <td>6.886678998909652e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>33.0</td>      <td>9.6</td>    <td>11.653154999217216</td> <td>0.26660604605480265</td> <td>11.127403216700957</td> <td>12.178906781733476</td>  <td>5.205556439853897</td> <td>18.100753558580536</td>  <td>-2.0531549992172167</td>   <td>3.247731907832487</td>  <td>-0.6321811828943349</td>   <td>0.0013465819158231121</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>34.0</td>     <td>17.4</td>    <td>19.658325248137746</td> <td>0.3935097036388686</td>   <td>18.88231723486466</td>  <td>20.43433326141083</td> <td>13.185512823654168</td> <td>26.131137672621325</td>  <td>-2.258325248137748</td>    <td>3.234809336280621</td>  <td>-0.698132413187099</td>    <td>0.003606277357289678</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>35.0</td>      <td>9.5</td>    <td>11.581850038567687</td> <td>0.2686588111783067</td>   <td>11.05205016734999</td> <td>12.111649909785385</td>  <td>5.133920126617092</td> <td>18.029779950518282</td>  <td>-2.081850038567687</td>   <td>3.2475627433696306</td>  <td>-0.6410499821190785</td>   <td>0.0014061798343687434</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>36.0</td>     <td>12.8</td>     <td>20.85149492300654</td> <td>0.44999608845434097</td>  <td>19.96409477161769</td>  <td>21.73889507439539</td> <td>14.364385298946695</td>  <td>27.33860454706639</td>   <td>-8.05149492300654</td>    <td>3.227436265725787</td>  <td>-2.4947029964651883</td>    <td>0.06049365563140271</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>37.0</td>     <td>25.4</td>    <td>19.720122880700668</td> <td>0.3963504164982569</td>   <td>18.93851293201936</td> <td>20.501732829381975</td> <td>13.246636466274317</td>  <td>26.19360929512702</td>   <td>5.679877119299331</td>   <td>3.2344625019140167</td>  <td>1.7560497659002765</td>     <td>0.02315250784150125</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>38.0</td>     <td>14.7</td>    <td>10.583580589474272</td> <td>0.30163053588852184</td>  <td>9.988759900853703</td>  <td>11.17840127809484</td> <td>4.1299828411252175</td> <td>17.037178337823327</td>   <td>4.116419410525728</td>   <td>3.2446664464572974</td>  <td>1.2686725980786893</td>    <td>0.006954719517408304</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>39.0</td>     <td>10.1</td>     <td>9.081422751790848</td> <td>0.36236534277464677</td>  <td>8.366831962477974</td>  <td>9.796013541103722</td>  <td>2.615685961443152</td> <td>15.547159542138544</td>  <td>1.0185772482091515</td>    <td>3.238446029703449</td>  <td>0.31452654725958934</td>   <td>0.0006193050202297058</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>40.0</td>     <td>21.5</td>    <td>17.870947567856202</td> <td>0.3170833704592719</td>   <td>17.24565361938004</td> <td>18.496241516332365</td>  <td>11.41446983089421</td> <td>24.327425304818192</td>   <td>3.629052432143798</td>    <td>3.24319278876918</td>   <td>1.1189752409140794</td>    <td>0.005984286248716949</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>41.0</td>     <td>16.6</td>     <td>16.6587632368142</td>  <td>0.2745161713429384</td>   <td>16.11741254897788</td> <td>17.200113924650516</td> <td>10.209873967094506</td> <td>23.107652506533892</td> <td>-0.058763236814197484</td>  <td>3.24707286653956</td>  <td>-0.018097295388637854</td> <td>1.1704399899586034e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>42.0</td>     <td>17.1</td>    <td>15.446578905772194</td> <td>0.24411306738888455</td>  <td>14.96518367031367</td> <td>15.927974141230719</td>  <td>9.002445634446476</td>  <td>21.89071217709791</td>  <td>1.6534210942278076</td>    <td>3.24949998296295</td>   <td>0.5088232352351607</td>    <td>0.0007305548898612851</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>43.0</td>     <td>20.7</td>     <td>20.9893511802623</td>  <td>0.4567157770970643</td>  <td>20.088699685424398</td> <td>21.890002675100202</td>  <td>14.50041556946767</td>  <td>27.47828679105693</td>  <td>-0.289351180262301</td>   <td>3.2264922172379165</td> <td>-0.08967980109061106</td>   <td>8.057309794728645e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>44.0</td>     <td>12.9</td>    <td>16.867924454719486</td> <td>0.2811268073543465</td>   <td>16.31353747712907</td>  <td>17.4223114323099</td>  <td>10.417927775122916</td> <td>23.317921134316055</td>  <td>-3.967924454719485</td>   <td>3.2465072073126486</td>  <td>-1.2222133515619087</td>   <td>0.005600616428800584</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>45.0</td>      <td>8.5</td>     <td>8.225763223996491</td> <td>0.40092817470111386</td>  <td>7.435125856129853</td>  <td>9.01640059186313</td>  <td>1.7511806356474926</td> <td>14.700345812345489</td>  <td>0.2742367760035087</td>    <td>3.233898255616131</td>  <td>0.08480068150791602</td>  <td>5.5264868222454676e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>46.0</td>     <td>14.9</td>    <td>15.356259288949456</td> <td>0.24247310180790985</td> <td>14.878098094279661</td> <td>15.834420483619251</td>  <td>8.912366802728648</td> <td>21.800151775170264</td> <td>-0.45625928894945567</td>  <td>3.2496227663908734</td>  <td>-0.1404037704524672</td>   <td>5.487680074899467e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>47.0</td>     <td>10.6</td>    <td>11.296630195969568</td> <td>0.2773056444855732</td>  <td>10.749778618342026</td>  <td>11.84348177359711</td>  <td>4.847276825759601</td> <td>17.745983566179536</td>  <td>-0.6966301959695684</td>  <td>3.2468358302326688</td> <td>-0.21455664295772164</td>  <td>0.00016789999936657073</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>48.0</td>     <td>23.2</td>    <td>18.436633589009137</td> <td>0.3398760946966982</td>   <td>17.76639198996932</td> <td>19.106875188048953</td> <td>11.975647902059476</td> <td>24.897619275958796</td>   <td>4.763366410990862</td>   <td>3.2408834550473955</td>   <td>1.469774052989265</td>    <td>0.011879155520486871</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>49.0</td>     <td>14.8</td>    <td>17.832918255509785</td> <td>0.31560856662235576</td> <td>17.210532645976397</td> <td>18.455303865043174</td> <td>11.376721535083806</td> <td>24.289114975935764</td>  <td>-3.0329182555097844</td>   <td>3.243336640193368</td>  <td>-0.9351228663482067</td>   <td>0.004140195671404474</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>50.0</td>      <td>9.7</td>    <td>10.212794794096718</td> <td>0.3155809884441276</td>   <td>9.590463569212801</td> <td>10.835126018980635</td>  <td>3.756603316193476</td>  <td>16.66898627199996</td>  <td>-0.5127947940967186</td>  <td>3.2433393237030947</td> <td>-0.15810704428891922</td>  <td>0.00011833394220962339</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>51.0</td>     <td>11.4</td>    <td>16.530414307645046</td> <td>0.2706361514056093</td>  <td>15.996715086939483</td> <td>17.064113528350607</td> <td>10.082162831154179</td> <td>22.978665784135913</td>  <td>-5.1304143076450455</td>   <td>3.247398559231463</td>  <td>-1.5798536009879927</td>   <td>0.008667705033990301</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>52.0</td>     <td>10.7</td>    <td>11.805272248602881</td> <td>0.26238066762043033</td> <td>11.287852986209666</td> <td>12.322691510996096</td>  <td>5.358347792788274</td> <td>18.252196704417486</td>  <td>-1.1052722486028816</td>  <td>3.2480760019133297</td>  <td>-0.3402852174492851</td>   <td>0.000377804799228125</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>53.0</td>     <td>22.6</td>    <td>17.319522538833173</td>  <td>0.296511235076766</td>  <td>16.734797200887677</td>  <td>17.90424787677867</td> <td>10.866847437240004</td>  <td>23.77219764042634</td>   <td>5.280477461166829</td>   <td>3.2451382738520516</td>   <td>1.627196444513529</td>    <td>0.011052636114460907</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>54.0</td>     <td>21.2</td>    <td>15.712784092197104</td> <td>0.24949388290448213</td> <td>15.220777794496822</td> <td>16.204790389897386</td>  <td>9.267849457706102</td> <td>22.157718726688106</td>   <td>5.487215907802895</td>   <td>3.2490912777789833</td>  <td>1.6888463384610886</td>    <td>0.008409036877530683</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>55.0</td>     <td>20.2</td>    <td>19.520468990881987</td> <td>0.38721149084178724</td> <td>18.756881163323865</td>  <td>20.28405681844011</td> <td>13.049133841449542</td> <td>25.991804140314432</td>   <td>0.679531009118012</td>    <td>3.235569283805603</td>  <td>0.21001899496300172</td>   <td>0.000315850975158325</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>56.0</td>     <td>23.7</td>    <td>16.487631331255326</td> <td>0.2693739310013705</td>  <td>15.956421231247802</td>  <td>17.01884143126285</td> <td>10.039585393435486</td> <td>22.935677269075164</td>  <td>7.2123686687446735</td>   <td>3.2475035048854206</td>   <td>2.220896346345635</td>    <td>0.016968304720845696</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>57.0</td>      <td>5.5</td>     <td>7.37961102428874</td>  <td>0.4409810905938851</td>   <td>6.509988606243345</td>  <td>8.249233442334134</td>  <td>0.894909381510403</td> <td>13.864312667067075</td>  <td>-1.8796110242887396</td>  <td>3.2286803816241783</td>  <td>-0.5821607598529795</td>   <td>0.0031611542402053307</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>58.0</td>     <td>13.2</td>    <td>13.507083976104987</td> <td>0.23226120044297419</td>  <td>13.04906082940876</td> <td>13.965107122801214</td>  <td>7.064654508210562</td>  <td>19.94951344399941</td>  <td>-0.3070839761049875</td>   <td>3.250368604283983</td>  <td>-0.0944766620315773</td>  <td>2.2788051365180094e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>59.0</td>     <td>23.8</td>    <td>17.053317352408264</td> <td>0.2872670705175079</td>  <td>16.486821668541598</td>  <td>17.61981303627493</td> <td>10.602268631020051</td> <td>23.504366073796476</td>  <td>6.7466826475917365</td>   <td>3.2459696485245377</td>  <td>2.0784798929523123</td>    <td>0.016917821612570865</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>60.0</td>     <td>18.4</td>    <td>17.048563688364958</td> <td>0.2871064774758367</td>  <td>16.482384696783285</td>  <td>17.61474267994663</td> <td>10.597542769441088</td> <td>23.499584607288828</td>   <td>1.351436311635041</td>    <td>3.245983856943475</td>  <td>0.41634104517931825</td>   <td>0.0006780500166182516</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>61.0</td>      <td>8.1</td>     <td>9.575803812294254</td>  <td>0.341233220960811</td>   <td>8.90288593654198</td>  <td>10.248721688046528</td> <td>3.1145399488235865</td>  <td>16.03706767576492</td>  <td>-1.475803812294254</td>   <td>3.2407408439828895</td>  <td>-0.4553908761431484</td>   <td>0.0011496156316605347</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>62.0</td>     <td>24.2</td>     <td>19.45391769427576</td> <td>0.38419073900607154</td> <td>18.696286842133865</td> <td>20.211548546417653</td> <td>12.983282736715399</td>  <td>25.92455265183612</td>   <td>4.74608230572424</td>     <td>3.235929357233898</td>  <td>1.4666829160267065</td>    <td>0.015161361070357792</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>63.0</td>     <td>15.7</td>    <td>18.408111604749326</td> <td>0.33869114320959387</td> <td>17.740206750752463</td>  <td>19.07601645874619</td> <td>11.947367906081386</td> <td>24.868855303417266</td>  <td>-2.7081116047493268</td>  <td>3.2410075036101964</td>  <td>-0.8355770857465554</td>    <td>0.00381233147456987</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>64.0</td>     <td>14.0</td>    <td>11.914606521598825</td> <td>0.2594776772245309</td>  <td>11.402912007004309</td> <td>12.426301036193342</td>  <td>5.468138998827067</td> <td>18.361074044370582</td>  <td>2.0853934784011745</td>   <td>3.2483092007948353</td>  <td>0.6419935263215999</td>    <td>0.0013149722276301157</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>65.0</td>     <td>18.0</td>    <td>13.264647109896586</td> <td>0.2343804345642502</td>  <td>12.802444796473582</td>  <td>13.72684942331959</td> <td>6.8219191764495655</td> <td>19.707375043343607</td>   <td>4.735352890103414</td>    <td>3.25021647599659</td>   <td>1.4569346149940512</td>    <td>0.0055191000002343974</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>66.0</td>      <td>9.3</td>     <td>10.31262173900606</td>  <td>0.311747535338661</td>   <td>9.69785015064658</td>   <td>10.92739332736554</td>  <td>3.857154571423301</td>  <td>16.76808890658882</td>  <td>-1.0126217390060592</td>   <td>3.243710036849239</td>  <td>-0.3121801047265199</td>   <td>0.0004500932048158166</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>67.0</td>      <td>9.5</td>     <td>8.529997722767819</td> <td>0.38696286430235893</td>  <td>7.766900191090901</td>  <td>9.293095254444736</td> <td>2.0587204076826175</td>  <td>15.00127503785302</td>  <td>0.9700022772321812</td>    <td>3.235599028093119</td>  <td>0.29979063190776345</td>   <td>0.0006427399652175256</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>68.0</td>     <td>13.4</td>     <td>13.65444756144735</td>  <td>0.231361578396908</td>   <td>13.19819848514941</td>  <td>14.11069663774529</td>  <td>7.212143977673325</td> <td>20.096751145221376</td>  <td>-0.2544475614473498</td>   <td>3.250432763339047</td> <td>-0.07828113361310247</td>  <td>1.5523309622667678e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>69.0</td>     <td>18.9</td>    <td>18.317791987926586</td> <td>0.3349624727729092</td>   <td>17.65724013719995</td> <td>18.978343838653224</td> <td>11.857804294951984</td>  <td>24.77777968090119</td>  <td>0.5822080120734121</td>    <td>3.241394988393127</td>  <td>0.17961649664980603</td>  <td>0.00017226253835179458</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>70.0</td>     <td>22.3</td>     <td>17.33853719500638</td> <td>0.29718976150769855</td>  <td>16.75247379107991</td>  <td>17.92460059893285</td> <td>10.885740703615474</td> <td>23.791333686397287</td>   <td>4.961462804993619</td>   <td>3.2450762047448465</td>  <td>1.5289202755051259</td>    <td>0.009802967696657618</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>71.0</td>     <td>18.3</td>    <td>16.497138659341932</td> <td>0.2696530557370028</td>  <td>15.965378120477245</td>  <td>17.02889919820662</td> <td>10.049047351320727</td> <td>22.945229967363137</td>   <td>1.802861340658069</td>    <td>3.247480339967883</td>  <td>0.5551569684563198</td>    <td>0.0010624762394747629</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>72.0</td>     <td>12.4</td>    <td>12.252116668673265</td> <td>0.2512672606662047</td>  <td>11.756613239032063</td> <td>12.747620098314467</td>  <td>5.806914119903279</td>  <td>18.69731921744325</td>  <td>0.14788333132673515</td>   <td>3.24895461535915</td>   <td>0.04551720440403494</td>  <td>6.1959183510719195e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>73.0</td>      <td>8.8</td>     <td>8.306575512732625</td> <td>0.39719371708069423</td> <td>7.5233025605636845</td>  <td>9.089848464901566</td> <td>1.8328880964694356</td> <td>14.780262928995814</td>  <td>0.49342448726737587</td>   <td>3.234359052433394</td>  <td>0.15255711541863118</td>  <td>0.00017549438315144227</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>74.0</td>     <td>11.0</td>    <td>13.183834821160453</td> <td>0.23526052824036658</td> <td>12.719896947626015</td>  <td>13.64777269469489</td>  <td>6.740982145801145</td>  <td>19.62668749651976</td>  <td>-2.1838348211604526</td>   <td>3.250152890680419</td>  <td>-0.6719175665312369</td>   <td>0.001182748888177972</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>75.0</td>     <td>17.0</td>    <td>17.176912617534114</td> <td>0.2914986113751585</td>   <td>16.60207226113799</td> <td>17.751752973930238</td> <td>10.725125757971366</td> <td>23.628699477096863</td> <td>-0.17691261753411425</td>   <td>3.245592378674897</td> <td>-0.05450857559825296</td>  <td>1.1983528185319118e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>76.0</td>      <td>8.7</td>     <td>7.83596277244573</td>   <td>0.419175232041962</td>   <td>7.009341888583902</td>  <td>8.662583656307557</td> <td>1.3568876585485743</td> <td>14.315037886342886</td>  <td>0.8640372275542694</td>   <td>3.2315837377033554</td>  <td>0.26737268710490836</td>   <td>0.0006014014692243932</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>77.0</td>      <td>6.9</td>     <td>8.339851161035739</td> <td>0.3956611236279878</td>   <td>7.559600509941949</td>  <td>9.120101812129528</td> <td>1.8665287278166725</td> <td>14.813173594254806</td>  <td>-1.4398511610357385</td>  <td>3.2345468931823604</td> <td>-0.44514771576525763</td>   <td>0.0014825118013199353</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>78.0</td>     <td>14.2</td>    <td>12.760758721306578</td> <td>0.24123509673811552</td> <td>12.285038894272063</td> <td>13.236478548341093</td>  <td>6.317046933856841</td> <td>19.204470508756316</td>  <td>1.4392412786934212</td>    <td>3.249714903964342</td>  <td>0.4428823208268775</td>    <td>0.0005404271433223485</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>79.0</td>      <td>5.3</td>     <td>7.289291407466003</td> <td>0.4453478594542656</td>   <td>6.411057644906277</td>  <td>8.167525170025728</td> <td>0.8034293377342738</td> <td>13.775153477197732</td>  <td>-1.9892914074660029</td>  <td>3.2280809489580222</td>  <td>-0.6162458249716809</td>   <td>0.0036139978447241373</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>80.0</td>     <td>11.0</td>    <td>12.546843839357988</td> <td>0.24509248698703084</td> <td>12.063517171333787</td>  <td>13.03017050738219</td>  <td>6.102565996658443</td> <td>18.991121682057532</td>  <td>-1.5468438393579884</td>   <td>3.249426257321242</td> <td>-0.47603598816031406</td>   <td>0.0006446087607764029</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>81.0</td>     <td>11.8</td>    <td>10.664392878210405</td> <td>0.2986993047482193</td>  <td>10.075352628630084</td> <td>11.253433127790727</td>  <td>4.211325339317714</td> <td>17.117460417103096</td>  <td>1.1356071217895956</td>   <td>3.2449376040671645</td>  <td>0.34996269893332915</td>   <td>0.0005188827602131547</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>82.0</td>     <td>12.3</td>    <td>18.431879924965834</td> <td>0.3396783570305652</td>   <td>17.76202826805966</td>  <td>19.10173158187201</td>  <td>11.97093467770171</td>  <td>24.89282517222996</td>  <td>-6.131879924965833</td>   <td>3.2409041859813192</td>  <td>-1.8920275247536051</td>   <td>0.019662026337524154</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>83.0</td>     <td>11.3</td>    <td>10.612102573734084</td> <td>0.30059130004127904</td>  <td>10.01933127636787</td> <td>11.204873871100299</td>  <td>4.158693392776614</td> <td>17.065511754691556</td>  <td>0.6878974262659163</td>   <td>3.2447628879913113</td>  <td>0.21200237120924517</td>   <td>0.0001928582947962124</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>84.0</td>     <td>13.6</td>    <td>10.284099754746247</td> <td>0.3128371875663688</td>   <td>9.667179353148967</td> <td>10.901020156343527</td> <td>3.8284275954903357</td>  <td>16.73977191400216</td>  <td>3.3159002452537525</td>    <td>3.243605127481116</td>  <td>1.0222885076731822</td>    <td>0.004860688060940899</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>85.0</td>     <td>21.7</td>    <td>17.181666281577414</td> <td>0.29166348775082296</td> <td>16.606500786086798</td>  <td>17.75683177706803</td>  <td>10.72985044469181</td> <td>23.633482118463018</td>   <td>4.518333718422586</td>   <td>3.2455775662983695</td>   <td>1.392150896450709</td>    <td>0.007825692360253335</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>86.0</td>     <td>15.2</td>    <td>16.216672480787114</td> <td>0.2617590214476864</td>  <td>15.700479115511579</td> <td>16.732865846062648</td>  <td>9.769846297599031</td> <td>22.663498663975197</td>  <td>-1.0166724807871148</td>  <td>3.2481261588240335</td>  <td>-0.3130027686963968</td>   <td>0.0003181294695379972</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>87.0</td>     <td>12.0</td>    <td>10.659639214167104</td> <td>0.2988705881279569</td>  <td>10.070261190768278</td>  <td>11.24901723756593</td>  <td>4.20654083429171</td>   <td>17.1127375940425</td>    <td>1.340360785832896</td>   <td>3.2449218327254465</td>  <td>0.41306412139583404</td>   <td>0.0007237070938355986</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>88.0</td>     <td>16.0</td>    <td>12.294899645062983</td> <td>0.25031140273964453</td> <td>11.801281183959285</td> <td>12.788518106166682</td>  <td>5.849841737563058</td>  <td>18.73995755256291</td>  <td>3.7051003549370165</td>    <td>3.249028397937564</td>   <td>1.140371797700802</td>    <td>0.0038593769118553827</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>89.0</td>     <td>12.9</td>     <td>11.23007889936334</td> <td>0.27941895990675775</td> <td>10.679059826789045</td> <td>11.781097971937635</td>  <td>4.780370823471411</td>  <td>17.67978697525527</td>  <td>1.6699211006366603</td>   <td>3.2466546434431316</td>  <td>0.5143513197528399</td>    <td>0.0009797815950864928</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>90.0</td>     <td>16.7</td>    <td>12.252116668673265</td> <td>0.2512672606662047</td>  <td>11.756613239032063</td> <td>12.747620098314467</td>  <td>5.806914119903279</td>  <td>18.69731921744325</td>   <td>4.447883331326734</td>    <td>3.24895461535915</td>   <td>1.3690198411205108</td>    <td>0.005604979258321018</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>91.0</td>     <td>11.2</td>     <td>13.41676435928225</td> <td>0.23295852018606372</td> <td>12.957366085865013</td> <td>13.876162632699488</td>  <td>6.974236981032029</td> <td>19.859291737532473</td>  <td>-2.2167643592822515</td>   <td>3.250318700807498</td>  <td>-0.6820144617607886</td>   <td>0.001194709938312947</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>92.0</td>      <td>7.3</td>     <td>8.392141465512061</td> <td>0.3932589196818065</td>   <td>7.616628002585463</td>  <td>9.16765492843866</td>  <td>1.9193883127133748</td> <td>14.864894618310748</td>  <td>-1.0921414655120616</td>   <td>3.234839833907843</td>  <td>-0.3376184051105559</td>   <td>0.0008423136354668727</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>93.0</td>     <td>19.4</td>    <td>17.381320171396098</td> <td>0.29872498806679837</td>  <td>16.79222927386265</td> <td>17.970411068929547</td> <td>10.928248009127827</td>  <td>23.83439233366437</td>  <td>2.0186798286039007</td>   <td>3.2449352397930395</td>  <td>0.6221017306751093</td>    <td>0.001639924524301346</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>94.0</td>     <td>22.2</td>    <td>18.959536633772355</td> <td>0.36218886330777356</td> <td>18.245293865052634</td> <td>19.673779402492077</td> <td>12.493838297277422</td>  <td>25.42523497026729</td>   <td>3.240463366227644</td>    <td>3.238465771973211</td>  <td>1.0006168335239856</td>    <td>0.006261770931113387</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>95.0</td>     <td>11.5</td>     <td>12.13802873163402</td> <td>0.25391154610652766</td>  <td>11.63731072488812</td> <td>12.638746738379918</td> <td>5.6924231923410264</td> <td>18.583634270927014</td>  <td>-0.6380287316340194</td>   <td>3.248749029349607</td>  <td>-0.1963921268986886</td>  <td>0.00011780147431573857</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>96.0</td>     <td>16.9</td>    <td>14.795326931839824</td> <td>0.23453702694117107</td> <td>14.332815815512635</td> <td>15.257838048167013</td>  <td>8.352576837461559</td>  <td>21.23807702621809</td>  <td>2.1046730681601744</td>    <td>3.250205179975538</td>  <td>0.6475508319065614</td>    <td>0.001091739467062788</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>97.0</td>     <td>11.7</td>     <td>16.4258336986924</td>   <td>0.267578902373186</td>  <td>15.898163426512868</td>  <td>16.95350397087193</td>  <td>9.978078417819301</td>  <td>22.8735889795655</td>   <td>-4.725833698692401</td>    <td>3.24765189944227</td>   <td>-1.455154014352334</td>    <td>0.007187083945269215</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>98.0</td>     <td>15.5</td>     <td>15.82211836519305</td> <td>0.2519317314441481</td>  <td>15.325304587564235</td> <td>16.318932142821865</td>  <td>9.376814945219191</td>  <td>22.26742178516691</td>  <td>-0.3221183651930506</td>   <td>3.248903158242451</td> <td>-0.09914680416861238</td>   <td>2.955423039734522e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>99.0</td>     <td>25.4</td>     <td>20.80395828257352</td> <td>0.44768710083095853</td> <td>19.921111495134085</td>  <td>21.68680507001296</td> <td>14.317469964848971</td> <td>27.290446600298072</td>   <td>4.596041717426477</td>   <td>3.2277573621162716</td>   <td>1.423911775826016</td>    <td>0.019502198364147585</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>100.0</td>    <td>17.2</td>    <td>13.459547335671967</td> <td>0.23261446703180713</td> <td>13.000827541088228</td> <td>13.918267130255707</td>  <td>7.017068302269696</td>  <td>19.90202636907424</td>   <td>3.740452664328032</td>   <td>3.2503433416600362</td>  <td>1.1507869388400318</td>    <td>0.003391367214284665</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>101.0</td>    <td>11.7</td>     <td>17.60474238143129</td> <td>0.3069279761329415</td>  <td>16.999475048060944</td> <td>18.210009714801636</td> <td>11.150173395764611</td>  <td>24.05931136709797</td>  <td>-5.904742381431291</td>   <td>3.2441696235574917</td>  <td>-1.8201090160496194</td>   <td>0.014826227186033991</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>102.0</td>    <td>23.8</td>    <td>21.122453773474753</td> <td>0.46323597170552633</td> <td>20.208944340910087</td>  <td>22.03596320603942</td> <td>14.631721015975831</td> <td>27.613186530973675</td>   <td>2.677546226525248</td>    <td>3.225562549922766</td>  <td>0.8301020938469662</td>    <td>0.0071060235003479735</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>103.0</td>    <td>14.8</td>    <td>20.352360198459834</td> <td>0.4259751671889789</td>   <td>19.51232972363995</td> <td>21.192390673279718</td> <td>13.871560599296853</td> <td>26.833159797622816</td>  <td>-5.552360198459834</td>    <td>3.230694427810303</td>  <td>-1.7186274723676378</td>   <td>0.025674991154379306</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>104.0</td>    <td>14.7</td>     <td>15.96472828649211</td> <td>0.25530205176981385</td> <td>15.461268178275182</td> <td>16.468188394709035</td>  <td>9.518909151079548</td>  <td>22.41054742190467</td>  <td>-1.2647282864921099</td>   <td>3.248640052592522</td>  <td>-0.3893100700654155</td>   <td>0.0004680224661052875</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>105.0</td>    <td>20.7</td>    <td>18.355821300273004</td> <td>0.33652800943251765</td>  <td>17.69218218389143</td> <td>19.019460416654578</td> <td>11.895517195768583</td> <td>24.816125404777424</td>  <td>2.3441786997269958</td>    <td>3.241232825301757</td>  <td>0.7232367515927383</td>    <td>0.0028193757136274296</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>106.0</td>    <td>19.2</td>    <td>13.587896264841122</td> <td>0.23173111866071008</td> <td>13.130918448684202</td> <td>14.044874080998042</td>  <td>7.145541030119547</td> <td>20.030251499562695</td>   <td>5.612103735158877</td>   <td>3.2504064388304545</td>  <td>1.7265852258089291</td>    <td>0.007575990513088951</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>107.0</td>     <td>7.2</td>     <td>8.22100955995319</td>  <td>0.40114839020725046</td>  <td>7.42993792325956</td>   <td>9.01208119664682</td>   <td>1.746373926941394</td> <td>14.695645192964985</td>  <td>-1.0210095599531899</td>   <td>3.233870946401596</td>  <td>-0.3157236565328283</td>   <td>0.0007669181049413794</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>108.0</td>     <td>8.7</td>    <td>11.329905844272682</td> <td>0.2762621852284508</td>  <td>10.785111986537592</td> <td>11.874699702007772</td>  <td>4.880726625696816</td> <td>17.779085062848548</td>  <td>-2.629905844272683</td>    <td>3.246924781075013</td>  <td>-0.8099682073330803</td>    <td>0.00237467608773187</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>109.0</td>     <td>5.3</td>     <td>7.655323538800254</td> <td>0.42775313731933673</td>  <td>6.81178687580824</td>   <td>8.498860201792269</td> <td>1.1740685409085154</td> <td>14.136578536691992</td>  <td>-2.3553235388002545</td>  <td>3.2304595002042182</td>  <td>-0.7290986123340533</td>   <td>0.0046601549075276005</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>110.0</td>    <td>19.8</td>    <td>19.173451515720945</td> <td>0.3716101895091366</td>  <td>18.440629727067762</td>  <td>19.90627330437413</td> <td>12.705674461754894</td> <td>25.641228569686994</td>  <td>0.6265484842790556</td>   <td>3.2373982139982727</td>  <td>0.19353457401993548</td>  <td>0.00024675735600242774</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>111.0</td>    <td>13.4</td>    <td>17.766366958903557</td> <td>0.3130465551754385</td>   <td>17.1490336807219</td>  <td>18.383700237085215</td> <td>11.310655331032045</td>  <td>24.22207858677507</td>  <td>-4.366366958903557</td>    <td>3.243584927705611</td>  <td>-1.3461546579550052</td>   <td>0.008439704321706164</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>112.0</td>    <td>21.8</td>    <td>18.522199541788574</td> <td>0.3434519494556111</td>  <td>17.844906294665986</td>  <td>19.19949278891116</td> <td>12.060478533536763</td> <td>24.983920550040384</td>   <td>3.277800458211427</td>   <td>3.2405064553802947</td>  <td>1.0115086957377333</td>     <td>0.00574665910602534</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>113.0</td>    <td>14.1</td>    <td>15.384781273209267</td> <td>0.2429805620236318</td>  <td>14.905619358124762</td> <td>15.863943188293772</td>  <td>8.940814452472805</td> <td>21.828748093945727</td>  <td>-1.2847812732092674</td>   <td>3.249584862013131</td> <td>-0.39536781704889534</td>   <td>0.0004369783622737221</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>114.0</td>    <td>15.9</td>     <td>16.99627338388864</td> <td>0.2853507333557592</td>  <td>16.433556750398363</td> <td>17.558990017378914</td> <td>10.545555419546098</td>  <td>23.44699134823118</td>  <td>-1.0962733838886383</td>    <td>3.2461386735504</td>   <td>-0.3377161280326977</td>   <td>0.0004406537350842214</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>115.0</td>    <td>14.6</td>    <td>10.749958830989842</td> <td>0.29564110853614506</td> <td>10.166949397790376</td> <td>11.332968264189308</td>  <td>4.297438994128858</td> <td>17.202478667850826</td>   <td>3.850041169010158</td>   <td>3.2452176604797622</td>  <td>1.1863737880808218</td>    <td>0.005840567835794737</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>116.0</td>    <td>12.6</td>     <td>10.60259524564748</td> <td>0.3009371485063063</td>   <td>10.00914192906355</td> <td>11.196048562231411</td>  <td>4.149123382777898</td> <td>17.056067108517063</td>  <td>1.9974047543525195</td>    <td>3.244730830376399</td>  <td>0.6155841142979539</td>    <td>0.0016298178301410236</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>117.0</td>    <td>12.2</td>    <td>13.649693897404045</td> <td>0.23138596005773326</td>  <td>13.19339674004482</td>  <td>14.10599105476327</td>  <td>7.207386908312402</td>  <td>20.09200088649569</td>  <td>-1.449693897404046</td>    <td>3.250431027792219</td> <td>-0.44600051039652966</td>   <td>0.0005040026416075556</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>118.0</td>     <td>9.4</td>    <td>10.664392878210405</td> <td>0.2986993047482193</td>  <td>10.075352628630084</td> <td>11.253433127790727</td>  <td>4.211325339317714</td> <td>17.117460417103096</td>  <td>-1.2643928782104048</td>  <td>3.2449376040671645</td>  <td>-0.3896509062687771</td>   <td>0.0006432460212329658</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>119.0</td>    <td>15.9</td>     <td>13.00794925155828</td> <td>0.23746948230624682</td> <td>12.539655281998193</td> <td>13.476243221118366</td>  <td>6.564781436902877</td> <td>19.451117066213683</td>  <td>2.8920507484417204</td>   <td>3.2499922421321905</td>  <td>0.8898638928886676</td>    <td>0.002113820654067064</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>120.0</td>     <td>6.6</td>     <td>7.954804373528279</td> <td>0.4135726956377144</td>  <td>7.1392317893758275</td>  <td>8.77037695768073</td>  <td>1.4771295680208247</td> <td>14.432479179035733</td>  <td>-1.354804373528279</td>    <td>3.232305516867051</td> <td>-0.41914490027583734</td>   <td>0.001438060930857408</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>121.0</td>    <td>15.5</td>     <td>13.74952084231339</td> <td>0.2309392435885814</td>  <td>13.294104617638967</td> <td>14.204937066987812</td>  <td>7.307276188189981</td> <td>20.191765496436798</td>  <td>1.7504791576866108</td>   <td>3.2504627970055213</td>  <td>0.5385322850946747</td>    <td>0.0007319789160448721</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>122.0</td>     <td>7.0</td>     <td>7.926282389268467</td> <td>0.4149142584172228</td>   <td>7.108064219867214</td>  <td>8.74450055866972</td>   <td>1.448273959309204</td> <td>14.404290819227729</td>  <td>-0.9262823892684668</td>   <td>3.232133581259956</td> <td>-0.28658542909212986</td>   <td>0.0006767314059286899</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>123.0</td>    <td>11.6</td>    <td>17.680801006124124</td> <td>0.3097887106366884</td>  <td>17.069892254312947</td>  <td>18.2917097579353</td>  <td>11.225700561597762</td> <td>24.135901450650486</td>  <td>-6.080801006124124</td>    <td>3.24389769932843</td>   <td>-1.8745353798866735</td>   <td>0.016023381116020145</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>124.0</td>    <td>15.2</td>    <td>12.884353986432428</td> <td>0.23925744573855715</td>  <td>12.4125341217341</td>  <td>13.356173851130757</td>  <td>6.440928947634438</td>  <td>19.32777902523042</td>   <td>2.315646013567571</td>   <td>3.2498611052789443</td>  <td>0.7125369172873661</td>    <td>0.001375897460036264</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>125.0</td>    <td>19.7</td>     <td>17.94225252850573</td> <td>0.31986934140182155</td>  <td>17.31146459663812</td>  <td>18.57304046037334</td> <td>11.485240397428791</td>  <td>24.39926465958267</td>  <td>1.7577474714942696</td>   <td>3.2429191993291147</td>  <td>0.5420262928098569</td>    <td>0.0014291693335091481</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>126.0</td>    <td>10.6</td>     <td>11.17778859488702</td> <td>0.2811036882179408</td>   <td>10.62344720863767</td> <td>11.732129981136369</td>  <td>4.727795833775285</td> <td>17.627781355998753</td>  <td>-0.5777885948870196</td>  <td>3.2465092091993966</td> <td>-0.17797226425533683</td>  <td>0.00011873382676060585</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>127.0</td>     <td>6.6</td>     <td>7.403379344505249</td> <td>0.4398346107966961</td>   <td>6.536017804657895</td>  <td>8.270740884352604</td> <td>0.9189805067800974</td> <td>13.887778182230402</td>  <td>-0.8033793445052497</td>  <td>3.2288367633083497</td> <td>-0.24881386189436422</td>   <td>0.000574388547403893</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>128.0</td>     <td>8.8</td>     <td>10.84503211185588</td> <td>0.29229970582109843</td> <td>10.268611983210969</td> <td>11.421452240500793</td>  <td>4.39310430610728</td>  <td>17.296959917604482</td>   <td>-2.04503211185588</td>   <td>3.2455203297658017</td>  <td>-0.6301091671188054</td>   <td>0.0016102365827143014</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>129.0</td>    <td>24.7</td>     <td>17.50491543652195</td> <td>0.30322506099398167</td> <td>16.906950316524572</td>  <td>18.10288055651933</td>  <td>11.05102711004632</td> <td>23.958803762997583</td>   <td>7.195084563478048</td>   <td>3.2445178210839614</td>   <td>2.217612896659708</td>    <td>0.021476887282717513</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>130.0</td>     <td>9.7</td>     <td>9.865777318935674</td> <td>0.3293141180417067</td>   <td>9.216364122459973</td> <td>10.515190515411375</td> <td>3.4069190803890406</td> <td>16.324635557482306</td>  <td>-0.1657773189356746</td>  <td>3.2419737106590847</td> <td>-0.05113468946112228</td>  <td>1.3489721137701748e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>131.0</td>     <td>1.6</td>     <td>7.06586919743081</td>  <td>0.45621641001737673</td>  <td>6.166202463201908</td>  <td>7.965535931659711</td> <td>0.5770701961854305</td>  <td>13.55466819867619</td>  <td>-5.465869197430809</td>    <td>3.226562864129115</td>  <td>-1.6940222235236404</td>    <td>0.02868598418321617</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>132.0</td>    <td>12.7</td>    <td>19.639310591964538</td> <td>0.3926377721902124</td>  <td>18.865022042747675</td>  <td>20.4135991411814</td>   <td>13.16670408427899</td> <td>26.111917099650086</td>  <td>-6.939310591964539</td>    <td>3.234915286185363</td>  <td>-2.1451289996986067</td>    <td>0.03389496283084112</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>133.0</td>     <td>5.7</td>     <td>7.431901328765061</td> <td>0.4384603265392408</td>  <td>6.5672499014929215</td>  <td>8.296552756037201</td> <td>0.9478644429532075</td> <td>13.915938214576915</td>  <td>-1.731901328765061</td>   <td>3.2290236714829645</td>  <td>-0.5363544851220203</td>   <td>0.002652112765811709</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>134.0</td>    <td>19.6</td>     <td>17.48114711630544</td> <td>0.3023522937331588</td>  <td>16.884903108600483</td> <td>18.077391124010397</td> <td>11.027418026654326</td> <td>23.934876205956556</td>  <td>2.1188528836945615</td>   <td>3.2445992694661876</td>  <td>0.6530399311971621</td>    <td>0.0018516286116830177</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>135.0</td>    <td>10.8</td>     <td>8.786695581106125</td> <td>0.3753899958416502</td>   <td>8.046419948302397</td>  <td>9.526971213909853</td>  <td>2.31806974106808</td>   <td>15.25532142114417</td>   <td>2.013304418893876</td>   <td>3.2369621066623915</td>   <td>0.621973428341977</td>    <td>0.0026013801693335024</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>136.0</td>    <td>11.6</td>     <td>9.32861328204255</td>  <td>0.3516797177560902</td>   <td>8.635094732027849</td> <td>10.022131832057251</td> <td>2.8651714570471842</td> <td>15.792055107037916</td>  <td>2.2713867179574496</td>    <td>3.239623852404044</td>  <td>0.7011266805780277</td>    <td>0.0028964661736946835</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>137.0</td>     <td>9.5</td>     <td>8.249531544213001</td> <td>0.39982799376203065</td>  <td>7.461063752387014</td>  <td>9.037999336038988</td> <td>1.7752135334390573</td> <td>14.723849554986945</td>   <td>1.250468455786999</td>    <td>3.234034462455595</td>  <td>0.38665897667569105</td>   <td>0.001142571290380754</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>138.0</td>    <td>20.8</td>    <td>20.043372035645206</td> <td>0.4113745472250223</td>  <td>19.232134238581455</td> <td>20.854609832708956</td> <td>13.566241574610029</td> <td>26.520502496680383</td>  <td>0.7566279643547951</td>    <td>3.232586009813448</td>  <td>0.23406274792312795</td>  <td>0.00044361810227685675</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>139.0</td>     <td>9.6</td>     <td>9.076669087747545</td> <td>0.36257304039261995</td>  <td>8.361668715101924</td>  <td>9.791669460393166</td> <td>2.6108870175901915</td>  <td>15.5424511579049</td>   <td>0.5233309122524545</td>   <td>3.2384227826716314</td>  <td>0.16160055291505743</td>  <td>0.00016367396887917625</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>140.0</td>    <td>20.7</td>     <td>15.82211836519305</td> <td>0.2519317314441481</td>  <td>15.325304587564235</td> <td>16.318932142821865</td>  <td>9.376814945219191</td>  <td>22.26742178516691</td>   <td>4.877881634806949</td>    <td>3.248903158242451</td>  <td>1.5013933617663509</td>    <td>0.006777213969135401</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>141.0</td>    <td>10.9</td>    <td>10.521782956911347</td> <td>0.3038994420474418</td>   <td>9.922487945689822</td> <td>11.121077968132871</td>  <td>4.067771277625359</td> <td>16.975794636197335</td>  <td>0.3782170430886538</td>   <td>3.2444547243056845</td>  <td>0.1165733768005015</td>    <td>5.961356957799329e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>142.0</td>    <td>19.2</td>    <td>16.240440801003622</td> <td>0.2623999737711761</td>  <td>15.722983466543708</td> <td>16.757898135463538</td>  <td>9.793513289477586</td> <td>22.687368312529657</td>   <td>2.959559198996377</td>    <td>3.248074442298253</td>   <td>0.911173451093156</td>    <td>0.0027092416581900197</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>143.0</td>    <td>20.1</td>    <td>17.514422764608554</td> <td>0.3035751346237533</td>  <td>16.915767293294735</td> <td>18.113078235922373</td> <td>11.060470439155653</td> <td>23.968375090061457</td>  <td>2.5855772353914475</td>    <td>3.244485084968706</td>   <td>0.796914508058645</td>    <td>0.002779932811581932</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>144.0</td>    <td>10.4</td>    <td>12.004926138421563</td> <td>0.2571671730367672</td>  <td>11.497787978467924</td> <td>12.512064298375202</td>  <td>5.558818680492702</td> <td>18.451033596350424</td>  <td>-1.604926138421563</td>   <td>3.2484929388962045</td>  <td>-0.4940525248507685</td>   <td>0.0007648626572711786</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>145.0</td>    <td>11.4</td>    <td>11.605618358784197</td> <td>0.26796954950758806</td> <td>11.077177723627958</td> <td>12.134058993940435</td>  <td>5.15779998736823</td>  <td>18.053436730200165</td> <td>-0.20561835878419643</td>   <td>3.24761968978557</td>  <td>-0.06331355836735082</td>  <td>1.3645957367980035e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>146.0</td>    <td>10.3</td>     <td>13.70198420188037</td> <td>0.23113484749545737</td> <td>13.246182242882856</td> <td>14.157786160877883</td> <td>7.2597122678720805</td>  <td>20.14425613588866</td>  <td>-3.401984201880369</td>   <td>3.2504488938021274</td>  <td>-1.0466198094568369</td>   <td>0.0027694407378722552</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>147.0</td>    <td>13.2</td>     <td>18.44614091709574</td> <td>0.34027186356043454</td> <td>17.775118854939453</td> <td>19.117162979252026</td> <td>11.985074220815209</td> <td>24.907207613376272</td>   <td>-5.24614091709574</td>   <td>3.2408419257679526</td>  <td>-1.6187586550839288</td>   <td>0.014443438395588919</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>148.0</td>    <td>25.4</td>     <td>18.5935045024381</td>  <td>0.3464553525595856</td>  <td>17.910288491901493</td>  <td>19.27672051297471</td> <td>12.131160008143597</td> <td>25.055848996732607</td>   <td>6.806495497561897</td>    <td>3.240186725734959</td>  <td>2.1006491519460213</td>    <td>0.025225020290373754</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>149.0</td>    <td>10.9</td>     <td>8.838985885582447</td> <td>0.37305792076713873</td>  <td>8.103309145585277</td>  <td>9.574662625579618</td> <td>2.3708847336478396</td> <td>15.307087037517055</td>   <td>2.061014114417553</td>   <td>3.2372317057478477</td>  <td>0.6366594367521273</td>    <td>0.0026914686524173803</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>150.0</td>    <td>10.1</td>     <td>9.157481376483679</td> <td>0.35905326222825923</td>  <td>8.449422067896274</td>  <td>9.865540685071084</td> <td>2.6924631839058577</td>  <td>15.6224995690615</td>    <td>0.942518623516321</td>   <td>3.2388149196626634</td>  <td>0.29100725015015316</td>   <td>0.0005203830162551537</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>151.0</td>    <td>16.1</td>    <td>20.376128518676342</td> <td>0.42710728034059214</td>  <td>19.53386549693459</td> <td>21.218391540418093</td> <td>13.895039162427775</td>  <td>26.85721787492491</td>  <td>-4.276128518676341</td>   <td>3.2305449540327222</td>  <td>-1.3236554759401833</td>   <td>0.015312365846202767</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>152.0</td>    <td>11.6</td>    <td>12.784527041523088</td> <td>0.24084026000728037</td>  <td>12.30958583942267</td> <td>13.259468243623505</td>  <td>6.340872690819792</td> <td>19.228181392226382</td>  <td>-1.1845270415230882</td>  <td>3.2497441896410626</td> <td>-0.36449854893160694</td>  <td>0.00036485595141336186</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>153.0</td>    <td>16.6</td>     <td>16.4258336986924</td>   <td>0.267578902373186</td>  <td>15.898163426512868</td>  <td>16.95350397087193</td>  <td>9.978078417819301</td>  <td>22.8735889795655</td>   <td>0.1741663013076007</td>    <td>3.24765189944227</td>   <td>0.05362837727082476</td>   <td>9.76166963855993e-06</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>154.0</td>    <td>19.0</td>    <td>15.175620055303982</td> <td>0.23948703649903916</td> <td>14.703347433613233</td> <td>15.647892676994731</td>  <td>8.732161847549115</td>  <td>21.61907826305885</td>   <td>3.824379944696018</td>    <td>3.249844194464579</td>  <td>1.1767887061201392</td>    <td>0.003760156552228026</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>155.0</td>    <td>15.6</td>    <td>15.959974622448808</td> <td>0.2551863114349744</td>  <td>15.456742756195075</td> <td>16.463206488702543</td>  <td>9.514173310191492</td> <td>22.405775934706124</td>  <td>-0.3599746224488083</td>   <td>3.248649146245626</td> <td>-0.11080747912245956</td>  <td>3.7880637794436625e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>156.0</td>     <td>3.2</td>     <td>7.227493774903077</td> <td>0.4483447287188032</td>  <td>6.3433501337749005</td>  <td>8.111637416031254</td>  <td>0.740828821012494</td>  <td>13.71415872879366</td>  <td>-4.027493774903077</td>    <td>3.227666081424205</td>  <td>-1.2478037297854392</td>   <td>0.015021368578435298</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>157.0</td>    <td>15.3</td>    <td>11.496284085788252</td> <td>0.2711809106498307</td>  <td>10.961510590331875</td>  <td>12.03105758124463</td>  <td>5.047943606461222</td> <td>17.944624565115284</td>  <td>3.8037159142117485</td>   <td>3.2473531133286615</td>   <td>1.171328088281965</td>    <td>0.004783946538392604</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>158.0</td>    <td>10.1</td>    <td>14.153582285994057</td> <td>0.23054121841672584</td> <td>13.698950973915151</td> <td>14.608213598072963</td>  <td>7.71139307146399</td>  <td>20.595771500524123</td>  <td>-4.053582285994057</td>    <td>3.250491051450096</td>  <td>-1.2470676651103805</td>   <td>0.003911553370696411</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>159.0</td>     <td>7.3</td>     <td>7.588772242194027</td> <td>0.43093152660356654</td>  <td>6.738967739982152</td>  <td>8.438576744405903</td> <td>1.1066985047343474</td> <td>14.070845979653708</td>  <td>-0.2887722421940273</td>  <td>3.2300370506118563</td> <td>-0.08940214544577005</td>   <td>7.113239215323387e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>160.0</td>    <td>12.9</td>    <td>13.293169094156397</td> <td>0.23409036278291606</td>  <td>12.83153880735601</td> <td>13.754799380956785</td>  <td>6.85048217272553</td>  <td>19.735856015587263</td>  <td>-0.3931690941563968</td>   <td>3.250237380715197</td> <td>-0.12096627049125934</td>  <td>3.7952072274045525e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>161.0</td>    <td>14.4</td>    <td>15.232664023823604</td> <td>0.24038703544473072</td>  <td>14.75861658848192</td>  <td>15.70671145916529</td>  <td>8.789075488167486</td>  <td>21.67625255947972</td>  <td>-0.8326640238236038</td>  <td>3.2497777465753432</td>  <td>-0.2562218369244099</td>   <td>0.0001796044312556081</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>162.0</td>    <td>13.3</td>     <td>11.10648363423749</td> <td>0.2834347148315913</td>  <td>10.547545422764726</td> <td>11.665421845710254</td>  <td>4.656094175442828</td> <td>17.556873093032152</td>  <td>2.1935163657625107</td>   <td>3.2463065307168013</td>   <td>0.675696008681648</td>    <td>0.0017402023184303506</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>163.0</td>    <td>14.9</td>    <td>15.988496606708619</td> <td>0.2558842119366363</td>   <td>15.48388846846782</td>  <td>16.49310474494942</td>  <td>9.542587701126429</td>  <td>22.43440551229081</td>  <td>-1.0884966067086186</td>   <td>3.248594249675971</td> <td>-0.33506696221517657</td>  <td>0.00034828058068680644</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>164.0</td>    <td>18.0</td>    <td>14.804834259926427</td> <td>0.23463798538373948</td> <td>14.342124051785959</td> <td>15.267544468066895</td>  <td>8.362069870116542</td>  <td>21.24759864973631</td>  <td>3.1951657400735733</td>   <td>3.2501978931691653</td>  <td>0.9830680608060046</td>    <td>0.0025183391117498777</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>165.0</td>    <td>11.9</td>    <td>12.603887807877612</td> <td>0.2440110746316296</td>  <td>12.122693703919008</td> <td>13.085081911836216</td>  <td>6.159769558530425</td>  <td>19.0480060572248</td>   <td>-0.7038878078776118</td>  <td>3.2495076433828154</td> <td>-0.21661367970959677</td>   <td>0.0001322896031844715</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>166.0</td>    <td>11.9</td>     <td>18.17993573067083</td> <td>0.32934295319774803</td>  <td>17.53046567076344</td>  <td>18.82940579057822</td> <td>11.721071774478453</td>  <td>24.63879968686321</td>  <td>-6.2799357306708306</td>  <td>3.2419707815039307</td>  <td>-1.9370735129690486</td>   <td>0.019361578793655417</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>167.0</td>     <td>8.0</td>    <td>7.8834994128787494</td> <td>0.41693022902485655</td>  <td>7.061305714204443</td>  <td>8.705693111553055</td>  <td>1.404987645194395</td> <td>14.362011180563105</td>  <td>0.11650058712125055</td>   <td>3.231874148705593</td>  <td>0.03604737739181785</td>  <td>1.0812727001237347e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>168.0</td>    <td>12.2</td>    <td>16.863170790676183</td> <td>0.28097275334880883</td>  <td>16.30908761027722</td> <td>17.417253971075144</td> <td>10.413200215806405</td>  <td>23.31314136554596</td>  <td>-4.663170790676183</td>   <td>3.2465205437239746</td>  <td>-1.4363595510556102</td>   <td>0.007726600205101863</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>169.0</td>    <td>17.1</td>    <td>17.271985898400153</td> <td>0.2948252755361554</td>   <td>16.69058530213566</td> <td>17.853386494664647</td> <td>10.819611227070098</td>  <td>23.72436056973021</td> <td>-0.17198589840015188</td>   <td>3.245291879916389</td> <td>-0.05299551003855557</td>  <td>1.1589642955285877e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>170.0</td>    <td>15.0</td>    <td>20.547260424235215</td> <td>0.4352943144091079</td>   <td>19.68885242821873</td>  <td>21.4056684202517</td>  <td>14.064053152096683</td> <td>27.030467696373748</td>  <td>-5.5472604242352155</td>  <td>3.2294519951207397</td>  <td>-1.7177095162325893</td>   <td>0.026802652178146695</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>171.0</td>     <td>8.4</td>     <td>9.409425570778684</td> <td>0.34823715018971363</td>   <td>8.7226958241735</td>  <td>10.096155317383866</td> <td>2.9467086505695557</td> <td>15.872142490987812</td>  <td>-1.0094255707786832</td>   <td>3.239995712369689</td> <td>-0.31155151438160483</td>   <td>0.0005606490192495998</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>172.0</td>    <td>14.5</td>    <td>14.852370900359446</td> <td>0.23516059899155817</td> <td>14.388630089050206</td> <td>15.316111711668686</td>  <td>8.409532412087474</td>  <td>21.29520938863142</td>  <td>-0.3523709003594462</td>   <td>3.250160122459839</td> <td>-0.10841647398367535</td>   <td>3.07666465400424e-05</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>173.0</td>     <td>7.6</td>     <td>7.964311701614883</td> <td>0.41312594180082135</td> <td>7.1496201238370745</td>  <td>8.779003279392692</td> <td>1.4867477603799513</td> <td>14.441875642849816</td> <td>-0.36431170161488335</td>  <td>3.2323626475315863</td> <td>-0.11270755832211223</td>  <td>0.00010375304748821606</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>174.0</td>    <td>11.7</td>    <td>15.037763798048225</td> <td>0.23747924507498622</td> <td>14.569450576137553</td> <td>15.506077019958896</td>  <td>8.594594584089826</td> <td>21.480933012006624</td>  <td>-3.3377637980482255</td>   <td>3.249991528774319</td>  <td>-1.0270069224786589</td>   <td>0.0028158116901326876</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>175.0</td>    <td>11.5</td>     <td>17.60474238143129</td> <td>0.3069279761329415</td>  <td>16.999475048060944</td> <td>18.210009714801636</td> <td>11.150173395764611</td>  <td>24.05931136709797</td>   <td>-6.10474238143129</td>   <td>3.2441696235574917</td>  <td>-1.8817580736536677</td>   <td>0.015847597222093227</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>176.0</td>    <td>27.0</td>    <td>20.195489285030867</td> <td>0.4185348707812062</td>  <td>19.370131204767375</td> <td>21.020847365294358</td> <td>13.716575162545436</td> <td>26.674403407516298</td>   <td>6.804510714969133</td>    <td>3.231666735739683</td>   <td>2.105573151995104</td>     <td>0.03718097998091955</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>177.0</td>    <td>20.2</td>    <td>18.840695032689805</td> <td>0.35702479736972564</td>  <td>18.1366358922566</td>   <td>19.54475417312301</td> <td>12.376113722263547</td> <td>25.305276343116063</td>  <td>1.3593049673101945</td>   <td>3.2390391512004495</td>  <td>0.41966302469867034</td>   <td>0.0010698817637108406</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>178.0</td>    <td>11.7</td>     <td>15.12332975082766</td> <td>0.2386974247957469</td>  <td>14.652614257216506</td> <td>15.594045244438814</td>  <td>8.679985485478298</td>  <td>21.56667401617702</td>  <td>-3.4233297508276603</td>  <td>3.2499022859683184</td>  <td>-1.0533639013111649</td>   <td>0.0029928277837426016</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>179.0</td>    <td>11.8</td>    <td>20.185981956944264</td> <td>0.4180857486119499</td>   <td>19.36150955344823</td>  <td>21.0104543604403</td>  <td>13.707180602526037</td>  <td>26.66478331136249</td>  <td>-8.385981956944264</td>   <td>3.2317248700583727</td>  <td>-2.5948935302753022</td>    <td>0.05634703364231869</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>180.0</td>    <td>12.6</td>    <td>14.904661204835769</td> <td>0.23576960300761832</td> <td>14.439719426962787</td>  <td>15.36960298270875</td>  <td>8.461736162380546</td>  <td>21.34758624729099</td>  <td>-2.304661204835769</td>   <td>3.2501160015057695</td>  <td>-0.7091012147775729</td>   <td>0.0013230137681933584</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>181.0</td>    <td>10.5</td>    <td>14.476831440938591</td> <td>0.23185230743654558</td> <td>14.019614638397606</td> <td>14.934048243479577</td>  <td>8.034459249702607</td> <td>20.919203632174575</td>  <td>-3.976831440938591</td>    <td>3.250397796652368</td>  <td>-1.223490689365587</td>    <td>0.0038082123479843324</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>182.0</td>    <td>12.2</td>    <td>17.419349483742515</td> <td>0.3000994445394886</td>   <td>16.8275481340224</td>   <td>18.01115083346263</td>  <td>10.96602932405607</td>  <td>23.87266964342896</td>  <td>-5.219349483742516</td>    <td>3.244808415351099</td>  <td>-1.6085231593489209</td>   <td>0.011065649362841374</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>183.0</td>     <td>8.7</td>     <td>9.704152741463407</td> <td>0.3359108039647808</td>   <td>9.041730765051623</td>  <td>10.36657471787519</td> <td>3.2439735550384494</td> <td>16.164331927888362</td>  <td>-1.0041527414634075</td>   <td>3.241296848597172</td> <td>-0.30979968462253105</td>   <td>0.0005153974645524297</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>184.0</td>    <td>26.2</td>     <td>20.70413133766418</td> <td>0.44285225058129574</td> <td>19.830818959419787</td> <td>21.577443715908572</td>  <td>14.21893382672592</td>  <td>27.18932884860244</td>   <td>5.49586866233582</td>     <td>3.228424261633112</td>  <td>1.7023378022675717</td>     <td>0.02726452891907084</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>185.0</td>    <td>17.6</td>     <td>19.09739289102811</td> <td>0.3682423911529699</td>  <td>18.371212459595107</td> <td>19.823573322461115</td> <td>12.630364959676557</td> <td>25.564420822379667</td>  <td>-1.4973928910281096</td>  <td>3.2377830177922924</td>  <td>-0.4624747497900951</td>   <td>0.0013833056116016916</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>186.0</td>    <td>22.6</td>    <td>16.777604837896746</td>  <td>0.278229689933718</td>  <td>16.228931026495147</td> <td>17.326278649298345</td>  <td>10.32809670182909</td> <td>23.227112973964402</td>  <td>5.8223951621032555</td>   <td>3.2467567769368877</td>   <td>1.793295760083489</td>    <td>0.011808134186751541</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>187.0</td>    <td>10.3</td>    <td>13.663954889533953</td> <td>0.2313137462695858</td>  <td>13.207800139027094</td>  <td>14.12010964004081</td>  <td>7.221657985300579</td> <td>20.106251793767328</td>  <td>-3.363954889533952</td>   <td>3.2504361676139637</td>  <td>-1.0349241505035673</td>    <td>0.00271210593212249</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>188.0</td>    <td>17.3</td>    <td>16.116845535877772</td> <td>0.25912598550638777</td> <td>15.605844563498243</td> <td>16.627846508257303</td>  <td>9.670433026608933</td>  <td>22.56325804514661</td>  <td>1.1831544641222287</td>   <td>3.2483372750657473</td>  <td>0.3642338722657059</td>    <td>0.0004221145948575232</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>189.0</td>    <td>15.9</td>     <td>20.62807271297135</td> <td>0.43918162206569866</td>  <td>19.76199887831435</td> <td>21.494146547628347</td> <td>14.143845994775692</td> <td>27.112299431167006</td>  <td>-4.728072712971349</td>    <td>3.228925646679707</td>  <td>-1.4642866483572359</td>    <td>0.01983327514827168</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>190.0</td>     <td>6.7</td>     <td>7.921528725225166</td> <td>0.41513804106234925</td>  <td>7.102869252536487</td>  <td>8.740188197913843</td> <td>1.4434645407555617</td>  <td>14.39959290969477</td>  <td>-1.2215287252251654</td>   <td>3.232104846042148</td>  <td>-0.3779359839520615</td>   <td>0.001178204492990001</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>191.0</td>    <td>10.8</td>     <td>8.910290846231977</td> <td>0.36989228808111174</td>  <td>8.180856789220053</td>   <td>9.6397249032439</td>  <td>2.4428967582384358</td> <td>15.377684934225517</td>   <td>1.889709153768024</td>   <td>3.2375949444246945</td>  <td>0.5836768299327254</td>    <td>0.002223414525516667</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>192.0</td>     <td>9.9</td>    <td>10.621609901820689</td> <td>0.30024601765763503</td> <td>10.029519507349807</td>  <td>11.21370029629157</td> <td>4.1682632288834895</td> <td>17.074956574757888</td>  <td>-0.7216099018206883</td>  <td>3.2447948560466733</td> <td>-0.22238999192074305</td>   <td>0.0002117290770624013</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>193.0</td>     <td>5.9</td>     <td>7.850223764575635</td> <td>0.4185011793359016</td>   <td>7.02493212443114</td>   <td>8.67551540472013</td>  <td>1.3713181056562735</td> <td>14.329129423494997</td>  <td>-1.950223764575635</td>    <td>3.231671098958042</td>  <td>-0.6034722299569494</td>   <td>0.003053680865926336</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>194.0</td>    <td>19.6</td>    <td>14.961705173355393</td> <td>0.23647443269852705</td> <td>14.495373459013042</td> <td>15.428036887697743</td>  <td>8.51867967956085</td>  <td>21.404730667149934</td>   <td>4.638294826644609</td>   <td>3.2500647949888832</td>   <td>1.427139186208278</td>    <td>0.005391219476520459</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>195.0</td>    <td>17.3</td>    <td>14.148828621950754</td> <td>0.23053271627215272</td> <td>13.694214076249546</td> <td>14.603443167651962</td>  <td>7.706640590617917</td>  <td>20.59101665328359</td>  <td>3.1511713780492467</td>   <td>3.2504916544538927</td>  <td>0.9694445373306665</td>    <td>0.002363648888386262</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>196.0</td>     <td>7.6</td>     <td>8.84849321366905</td>  <td>0.3726348646458637</td>   <td>8.113650747737138</td>  <td>9.583335679600962</td> <td>2.3804868983024807</td>  <td>15.31649952903562</td>  <td>-1.2484932136690503</td>  <td>3.2372804306387453</td>  <td>-0.3856611252620803</td>   <td>0.0009853444184807923</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>197.0</td>     <td>9.7</td>    <td>11.510545077918158</td> <td>0.27075617630292786</td> <td>10.976609166017308</td> <td>12.044480989819007</td>  <td>5.062274007010676</td>  <td>17.95881614882564</td>  <td>-1.8105450779181584</td>   <td>3.247388554198595</td>  <td>-0.5575387877675676</td>   <td>0.0010804592962577679</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>198.0</td>    <td>12.8</td>    <td>15.446578905772194</td> <td>0.24411306738888455</td>  <td>14.96518367031367</td> <td>15.927974141230719</td>  <td>9.002445634446476</td>  <td>21.89071217709791</td>  <td>-2.646578905772193</td>    <td>3.24949998296295</td>   <td>-0.8144572763957972</td>   <td>0.0018717834254780047</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>199.0</td>    <td>25.5</td>     <td>20.5139847759321</td>   <td>0.43369755251424</td>   <td>19.658725622280237</td> <td>21.369243929583966</td> <td>14.031193674424184</td>  <td>26.99677587744002</td>  <td>4.9860152240678985</td>    <td>3.229666819021643</td>  <td>1.5438172119495295</td>    <td>0.021489200634195436</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>200.0</td>    <td>13.4</td>    <td>18.065847793631583</td> <td>0.3247605614135507</td>  <td>17.425414290412913</td> <td>18.706281296850253</td> <td>11.607886248536268</td>  <td>24.5238093387269</td>   <td>-4.665847793631583</td>   <td>3.2424330227001725</td>  <td>-1.4389958901128037</td>   <td>0.010386605835451347</td> \n",
       "</tr>\n",
       "</table>"
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{cccccccccccc}\n",
       "\\toprule\n",
       "\\textbf{Obs} &   \\textbf{Dep Var}  & \\textbf{Predicted} &   \\textbf{Std Error}  &  \\textbf{Mean ci}  &  \\textbf{Mean ci}  & \\textbf{Predict ci} & \\textbf{Predict ci} &   \\textbf{Residual}   & \\textbf{Std Error} &    \\textbf{Student}   &    \\textbf{Cook's}      \\\\\n",
       " \\textbf{}   & \\textbf{Population} &   \\textbf{Value}   & \\textbf{Mean Predict} & \\textbf{95\\% low}  & \\textbf{95\\% upp}  &  \\textbf{95\\% low}  &  \\textbf{95\\% upp}  &       \\textbf{}       & \\textbf{Residual}  &   \\textbf{Residual}   &       \\textbf{D}        \\\\\n",
       "\\midrule\n",
       "    1.0      &         22.1        & 17.970774512765544 &  0.32099116790047916  & 17.337774319435486 & 18.603774706095603 &  11.513545889691956 &  24.428003135839134 &   4.129225487234457   & 3.2428083506547387 &   1.2733486042740534  &  0.00794343302166503    \\\\\n",
       "    2.0      &         10.4        & 9.147974048397074  &  0.35946612171373415  & 8.439100573688425  & 9.856847523105724  &  2.6828666363713127 &  15.613081460422837 &   1.252025951602926   & 3.2387691236465606 &  0.38657462258169806  & 0.0009204339664699191   \\\\\n",
       "    3.0      &         9.3         & 7.850223764575635  &   0.4185011793359016  &  7.02493212443114  &  8.67551540472013  &  1.3713181056562735 &  14.329129423494997 &   1.4497762354243653  & 3.231671098958042  &   0.4486150326039686  & 0.0016875502454444286   \\\\\n",
       "    4.0      &         18.5        & 14.23439457473019  &  0.23073371631706893  & 13.779383653427363 & 14.689405496033018 &  7.792178559693922  &  20.676610589766458 &   4.2656054252698095  & 3.250477392799515  &   1.3123012129599836  &  0.004338752604050602   \\\\\n",
       "    5.0      &         12.9        & 15.62721813941767  &  0.24767713560076052  & 15.138794499153134 & 16.115641779682203 &  9.182556014972805  &  22.071880263862532 &   -2.727218139417669  & 3.249230272764124  &  -0.8393428321402476  &  0.002046725626794406   \\\\\n",
       "    6.0      &         7.2         & 7.446162320894968  &  0.43777379903907726  & 6.582864737852164  & 8.309459903937771  &  0.9623058324482594 &  13.930018809341675 &  -0.24616232089496748 & 3.229116818856375  &  -0.07623208905218498 & 5.340447673606104e-05   \\\\\n",
       "    7.0      &         11.8        & 9.765950374026332  &  0.33337431369247794  & 9.108530400763886  & 10.423370347288778 &  3.3062821730171406 &  16.225618575035522 &   2.034049625973669   & 3.2415587139393742 &   0.6274912181065344  &  0.002082292779658906   \\\\\n",
       "    8.0      &         13.2        & 12.74649772917667  &  0.24147528648095948  & 12.270304243771271 & 13.22269121458207  &  6.302750955642853  &  19.190244502710488 &   0.4535022708233285  & 3.249697065107017  &  0.13955216801366502  & 5.3765390400867915e-05  \\\\\n",
       "    9.0      &         4.8         & 7.4414086568516655 &  0.43800259582072804  & 6.577659882556574  & 8.305157431146757  &  0.9574920788117227 &  13.92532523489161  &  -2.6414086568516657  & 3.2290857924497027 &  -0.8180051031867432  &  0.006155682784170733   \\\\\n",
       "    10.0     &         10.6        & 16.530414307645046 &   0.2706361514056093  & 15.996715086939483 & 17.064113528350607 &  10.082162831154179 &  22.978665784135913 &   -5.930414307645046  & 3.247398559231463  &  -1.8262046371815082  &  0.011581620158297331   \\\\\n",
       "    11.0     &         8.6         & 10.174765481750303 &  0.31705564656532703  & 9.549526205277552  & 10.800004758223054 &  3.718293039407727  &  16.63123792409288  &   -1.574765481750303  & 3.2431954991839858 &  -0.4855598381739635  & 0.0011266272392702998   \\\\\n",
       "    12.0     &         17.4        & 17.23871025009704  &   0.2936540129804136  &  16.6596194040636  & 17.817801096130477 &  10.786543292101868 &  23.69087720809221  &   0.1612897499029593  & 3.2453980725955205 &  0.049697986593665276 & 1.0110753583244568e-05  \\\\\n",
       "    13.0     &         9.2         & 8.163965591433566  &   0.4037955927680105  & 7.367673625022752  &  8.96025755784438  &  1.688690065121552  &  14.63924111774558  &   1.036034408566433   &  3.23354147154592  &  0.32040238781014196  & 0.0008004381338116445   \\\\\n",
       "    14.0     &         9.7         & 11.667415991347122 &   0.2662009362211627  & 11.142463092503244 &  12.192368890191   &  5.219882525603069  &  18.114949457091175 &  -1.9674159913471225  & 3.247765137829581  &  -0.6057753279111521  & 0.0012326594024323152   \\\\\n",
       "    15.0     &         19.0        & 16.73482186150703  &   0.2768797358793503  & 16.18881018309492  & 17.28083353991914  &  10.285539653474313 &  23.184104069539746 &   2.2651781384929706  & 3.246872178082408  &   0.6976493111689962  & 0.0017696863630991143   \\\\\n",
       "    16.0     &         22.4        & 16.32125308973976  &   0.2646187608915433  & 15.799420268298887 & 16.84308591118063  &  9.873972908188946  &  22.768533271290572 &   6.078746910260239   & 3.2478944318327905 &   1.871596210357735   &  0.011626038913078581   \\\\\n",
       "    17.0     &         12.5        & 10.255577770486436 &   0.3139313593819662  & 9.636499642945045  & 10.874655898027827 &  3.799699056176115  &  16.711456484796756 &   2.244422229513564   & 3.243499411213576  &   0.6919755316600471  &  0.002242813878073586   \\\\\n",
       "    18.0     &         24.4        & 20.409404166979456 &   0.4286943085577553  & 19.564011497855645 & 21.254796836103267 &  13.92790734827367  &  26.890900985685242 &   3.990595833020542   & 3.230334737880334  &   1.2353505617312812  &  0.013438500709651345   \\\\\n",
       "    19.0     &         11.3        & 10.322129067092664 &   0.3113853304886954  & 9.708071753027873  & 10.936186381157455 &  3.8667298826237904 &  16.777528251561538 &   0.9778709329073365  & 3.243744827341181  &  0.30146358143370783  & 0.00041873826137191417  \\\\\n",
       "    20.0     &         14.6        & 14.034740684911508 &  0.23042284318185957  & 13.580342810864702 & 14.489138558958315 &  7.5925679401131205 &  20.476913429709896 &   0.5652593150884915  & 3.250499445052438  &  0.17389921907197017  & 7.598294766503545e-05   \\\\\n",
       "    21.0     &         18.0        & 17.414595819699212 &  0.29992713713924213  & 16.823134263183942 & 18.006057376214482 &  10.961306811858297 &  23.867884827540127 &   0.5854041803007881  & 3.244824346764194  &  0.18041167032186667  & 0.00013904276624749297  \\\\\n",
       "    22.0     &         12.5        & 18.317791987926586 &   0.3349624727729092  & 17.65724013719995  & 18.978343838653224 &  11.857804294951984 &  24.77777968090119  &  -5.8177919879265865  & 3.241394988393127  &  -1.7948420383072998  &  0.01720088789738924    \\\\\n",
       "    23.0     &         5.6         & 7.660077202843556  &   0.4275264753161854  & 6.816987521283317  & 8.503166884403795  &  1.1788803645243968 &  14.141274041162717 &  -2.0600772028435568  & 3.2304895049899076 &  -0.6376981567844445  & 0.0035611452472006605   \\\\\n",
       "    24.0     &         15.5        & 17.885208559986108 &   0.3176384170705466  & 17.258820049891497 & 18.511597070080718 &  11.428624725521981 &  24.341792394450234 &  -2.3852085599861077  & 3.2431384745254306 &  -0.7354630641650711  & 0.0025943394475503477   \\\\\n",
       "    25.0     &         9.7         & 9.994126248104827  &   0.324163863230972   & 9.354869444131193  & 10.633383052078461 &  3.536281289659981  &  16.451971206549672 &  -0.2941262481048277  & 3.242492732254213  &  -0.09070991745919757 & 4.111977447400488e-05   \\\\\n",
       "    26.0     &         12.0        & 19.52997631896859  &  0.38764409327620025  & 18.76553539184885  & 20.29441724608833  &  13.05854045225859  &  26.00141218567859  &   -7.52997631896859   & 3.2355174834783837 &   -2.327286549190083  &  0.038873045173275146   \\\\\n",
       "    27.0     &         15.0        & 13.82557946700622  &  0.23069121439746448  & 13.370652360231693 & 14.280506573780746 &  7.383369371211208  &  20.267789562801234 &   1.1744205329937802  & 3.250480409500424  &   0.3613067562447732  & 0.0003287677234890113   \\\\\n",
       "    28.0     &         15.9        & 18.44614091709574  &  0.34027186356043454  & 17.775118854939453 & 19.117162979252026 &  11.985074220815209 &  24.907207613376272 &   -2.546140917095739  & 3.2408419257679526 &  -0.7856418101886915  &  0.003402166482447813   \\\\\n",
       "    29.0     &         18.9        & 18.859709688863013 &  0.35784755909653243  & 18.154028047924452 & 19.565391329801574 &  12.394951470318205 &  25.324467907407822 &  0.040290311136985224 & 3.2389483560864125 &  0.012439318787307736 & 9.443897647389483e-07   \\\\\n",
       "    30.0     &         10.5        & 10.38868036369889  &  0.30886425497699127  & 9.779594654606118  & 10.997766072791663 &   3.93375219625148  &   16.8436085311463  &  0.11131963630110953  & 3.2439858509160806 &  0.03431569723698812  & 5.337440623893835e-06   \\\\\n",
       "    31.0     &         21.4        & 20.956075531959183 &   0.4550906188776845  & 20.058628877534144 & 21.85352218638422  &  14.467583970477143 &  27.444567093441222 &  0.44392446804081587  & 3.2267218438464367 &   0.1375775444937741  & 0.00018825122895388218  \\\\\n",
       "    32.0     &         11.9        & 12.399480254015627 &  0.24805888698623182  & 11.910303793346754 &  12.8886567146845  &   5.95476103161676  &  18.844199476414495 &  -0.49948025401562646 & 3.2492011506727887 &  -0.15372401733644675 & 6.886678998909652e-05   \\\\\n",
       "    33.0     &         9.6         & 11.653154999217216 &  0.26660604605480265  & 11.127403216700957 & 12.178906781733476 &  5.205556439853897  &  18.100753558580536 &  -2.0531549992172167  & 3.247731907832487  &  -0.6321811828943349  & 0.0013465819158231121   \\\\\n",
       "    34.0     &         17.4        & 19.658325248137746 &   0.3935097036388686  & 18.88231723486466  & 20.43433326141083  &  13.185512823654168 &  26.131137672621325 &   -2.258325248137748  & 3.234809336280621  &   -0.698132413187099  &  0.003606277357289678   \\\\\n",
       "    35.0     &         9.5         & 11.581850038567687 &   0.2686588111783067  & 11.05205016734999  & 12.111649909785385 &  5.133920126617092  &  18.029779950518282 &   -2.081850038567687  & 3.2475627433696306 &  -0.6410499821190785  & 0.0014061798343687434   \\\\\n",
       "    36.0     &         12.8        & 20.85149492300654  &  0.44999608845434097  & 19.96409477161769  & 21.73889507439539  &  14.364385298946695 &  27.33860454706639  &   -8.05149492300654   & 3.227436265725787  &  -2.4947029964651883  &  0.06049365563140271    \\\\\n",
       "    37.0     &         25.4        & 19.720122880700668 &   0.3963504164982569  & 18.93851293201936  & 20.501732829381975 &  13.246636466274317 &  26.19360929512702  &   5.679877119299331   & 3.2344625019140167 &   1.7560497659002765  &  0.02315250784150125    \\\\\n",
       "    38.0     &         14.7        & 10.583580589474272 &  0.30163053588852184  & 9.988759900853703  & 11.17840127809484  &  4.1299828411252175 &  17.037178337823327 &   4.116419410525728   & 3.2446664464572974 &   1.2686725980786893  &  0.006954719517408304   \\\\\n",
       "    39.0     &         10.1        & 9.081422751790848  &  0.36236534277464677  & 8.366831962477974  & 9.796013541103722  &  2.615685961443152  &  15.547159542138544 &   1.0185772482091515  & 3.238446029703449  &  0.31452654725958934  & 0.0006193050202297058   \\\\\n",
       "    40.0     &         21.5        & 17.870947567856202 &   0.3170833704592719  & 17.24565361938004  & 18.496241516332365 &  11.41446983089421  &  24.327425304818192 &   3.629052432143798   &  3.24319278876918  &   1.1189752409140794  &  0.005984286248716949   \\\\\n",
       "    41.0     &         16.6        &  16.6587632368142  &   0.2745161713429384  & 16.11741254897788  & 17.200113924650516 &  10.209873967094506 &  23.107652506533892 & -0.058763236814197484 &  3.24707286653956  & -0.018097295388637854 & 1.1704399899586034e-06  \\\\\n",
       "    42.0     &         17.1        & 15.446578905772194 &  0.24411306738888455  & 14.96518367031367  & 15.927974141230719 &  9.002445634446476  &  21.89071217709791  &   1.6534210942278076  &  3.24949998296295  &   0.5088232352351607  & 0.0007305548898612851   \\\\\n",
       "    43.0     &         20.7        &  20.9893511802623  &   0.4567157770970643  & 20.088699685424398 & 21.890002675100202 &  14.50041556946767  &  27.47828679105693  &   -0.289351180262301  & 3.2264922172379165 &  -0.08967980109061106 & 8.057309794728645e-05   \\\\\n",
       "    44.0     &         12.9        & 16.867924454719486 &   0.2811268073543465  & 16.31353747712907  &  17.4223114323099  &  10.417927775122916 &  23.317921134316055 &   -3.967924454719485  & 3.2465072073126486 &  -1.2222133515619087  &  0.005600616428800584   \\\\\n",
       "    45.0     &         8.5         & 8.225763223996491  &  0.40092817470111386  & 7.435125856129853  &  9.01640059186313  &  1.7511806356474926 &  14.700345812345489 &   0.2742367760035087  & 3.233898255616131  &  0.08480068150791602  & 5.5264868222454676e-05  \\\\\n",
       "    46.0     &         14.9        & 15.356259288949456 &  0.24247310180790985  & 14.878098094279661 & 15.834420483619251 &  8.912366802728648  &  21.800151775170264 &  -0.45625928894945567 & 3.2496227663908734 &  -0.1404037704524672  & 5.487680074899467e-05   \\\\\n",
       "    47.0     &         10.6        & 11.296630195969568 &   0.2773056444855732  & 10.749778618342026 & 11.84348177359711  &  4.847276825759601  &  17.745983566179536 &  -0.6966301959695684  & 3.2468358302326688 &  -0.21455664295772164 & 0.00016789999936657073  \\\\\n",
       "    48.0     &         23.2        & 18.436633589009137 &   0.3398760946966982  & 17.76639198996932  & 19.106875188048953 &  11.975647902059476 &  24.897619275958796 &   4.763366410990862   & 3.2408834550473955 &   1.469774052989265   &  0.011879155520486871   \\\\\n",
       "    49.0     &         14.8        & 17.832918255509785 &  0.31560856662235576  & 17.210532645976397 & 18.455303865043174 &  11.376721535083806 &  24.289114975935764 &  -3.0329182555097844  & 3.243336640193368  &  -0.9351228663482067  &  0.004140195671404474   \\\\\n",
       "    50.0     &         9.7         & 10.212794794096718 &   0.3155809884441276  & 9.590463569212801  & 10.835126018980635 &  3.756603316193476  &  16.66898627199996  &  -0.5127947940967186  & 3.2433393237030947 &  -0.15810704428891922 & 0.00011833394220962339  \\\\\n",
       "    51.0     &         11.4        & 16.530414307645046 &   0.2706361514056093  & 15.996715086939483 & 17.064113528350607 &  10.082162831154179 &  22.978665784135913 &  -5.1304143076450455  & 3.247398559231463  &  -1.5798536009879927  &  0.008667705033990301   \\\\\n",
       "    52.0     &         10.7        & 11.805272248602881 &  0.26238066762043033  & 11.287852986209666 & 12.322691510996096 &  5.358347792788274  &  18.252196704417486 &  -1.1052722486028816  & 3.2480760019133297 &  -0.3402852174492851  &  0.000377804799228125   \\\\\n",
       "    53.0     &         22.6        & 17.319522538833173 &   0.296511235076766   & 16.734797200887677 & 17.90424787677867  &  10.866847437240004 &  23.77219764042634  &   5.280477461166829   & 3.2451382738520516 &   1.627196444513529   &  0.011052636114460907   \\\\\n",
       "    54.0     &         21.2        & 15.712784092197104 &  0.24949388290448213  & 15.220777794496822 & 16.204790389897386 &  9.267849457706102  &  22.157718726688106 &   5.487215907802895   & 3.2490912777789833 &   1.6888463384610886  &  0.008409036877530683   \\\\\n",
       "    55.0     &         20.2        & 19.520468990881987 &  0.38721149084178724  & 18.756881163323865 & 20.28405681844011  &  13.049133841449542 &  25.991804140314432 &   0.679531009118012   & 3.235569283805603  &  0.21001899496300172  &  0.000315850975158325   \\\\\n",
       "    56.0     &         23.7        & 16.487631331255326 &   0.2693739310013705  & 15.956421231247802 & 17.01884143126285  &  10.039585393435486 &  22.935677269075164 &   7.2123686687446735  & 3.2475035048854206 &   2.220896346345635   &  0.016968304720845696   \\\\\n",
       "    57.0     &         5.5         &  7.37961102428874  &   0.4409810905938851  & 6.509988606243345  & 8.249233442334134  &  0.894909381510403  &  13.864312667067075 &  -1.8796110242887396  & 3.2286803816241783 &  -0.5821607598529795  & 0.0031611542402053307   \\\\\n",
       "    58.0     &         13.2        & 13.507083976104987 &  0.23226120044297419  & 13.04906082940876  & 13.965107122801214 &  7.064654508210562  &  19.94951344399941  &  -0.3070839761049875  & 3.250368604283983  &  -0.0944766620315773  & 2.2788051365180094e-05  \\\\\n",
       "    59.0     &         23.8        & 17.053317352408264 &   0.2872670705175079  & 16.486821668541598 & 17.61981303627493  &  10.602268631020051 &  23.504366073796476 &   6.7466826475917365  & 3.2459696485245377 &   2.0784798929523123  &  0.016917821612570865   \\\\\n",
       "    60.0     &         18.4        & 17.048563688364958 &   0.2871064774758367  & 16.482384696783285 & 17.61474267994663  &  10.597542769441088 &  23.499584607288828 &   1.351436311635041   & 3.245983856943475  &  0.41634104517931825  & 0.0006780500166182516   \\\\\n",
       "    61.0     &         8.1         & 9.575803812294254  &   0.341233220960811   &  8.90288593654198  & 10.248721688046528 &  3.1145399488235865 &  16.03706767576492  &   -1.475803812294254  & 3.2407408439828895 &  -0.4553908761431484  & 0.0011496156316605347   \\\\\n",
       "    62.0     &         24.2        & 19.45391769427576  &  0.38419073900607154  & 18.696286842133865 & 20.211548546417653 &  12.983282736715399 &  25.92455265183612  &    4.74608230572424   & 3.235929357233898  &   1.4666829160267065  &  0.015161361070357792   \\\\\n",
       "    63.0     &         15.7        & 18.408111604749326 &  0.33869114320959387  & 17.740206750752463 & 19.07601645874619  &  11.947367906081386 &  24.868855303417266 &  -2.7081116047493268  & 3.2410075036101964 &  -0.8355770857465554  &  0.00381233147456987    \\\\\n",
       "    64.0     &         14.0        & 11.914606521598825 &   0.2594776772245309  & 11.402912007004309 & 12.426301036193342 &  5.468138998827067  &  18.361074044370582 &   2.0853934784011745  & 3.2483092007948353 &   0.6419935263215999  & 0.0013149722276301157   \\\\\n",
       "    65.0     &         18.0        & 13.264647109896586 &   0.2343804345642502  & 12.802444796473582 & 13.72684942331959  &  6.8219191764495655 &  19.707375043343607 &   4.735352890103414   &  3.25021647599659  &   1.4569346149940512  & 0.0055191000002343974   \\\\\n",
       "    66.0     &         9.3         & 10.31262173900606  &   0.311747535338661   &  9.69785015064658  & 10.92739332736554  &  3.857154571423301  &  16.76808890658882  &  -1.0126217390060592  & 3.243710036849239  &  -0.3121801047265199  & 0.0004500932048158166   \\\\\n",
       "    67.0     &         9.5         & 8.529997722767819  &  0.38696286430235893  & 7.766900191090901  & 9.293095254444736  &  2.0587204076826175 &  15.00127503785302  &   0.9700022772321812  & 3.235599028093119  &  0.29979063190776345  & 0.0006427399652175256   \\\\\n",
       "    68.0     &         13.4        & 13.65444756144735  &   0.231361578396908   & 13.19819848514941  & 14.11069663774529  &  7.212143977673325  &  20.096751145221376 &  -0.2544475614473498  & 3.250432763339047  &  -0.07828113361310247 & 1.5523309622667678e-05  \\\\\n",
       "    69.0     &         18.9        & 18.317791987926586 &   0.3349624727729092  & 17.65724013719995  & 18.978343838653224 &  11.857804294951984 &  24.77777968090119  &   0.5822080120734121  & 3.241394988393127  &  0.17961649664980603  & 0.00017226253835179458  \\\\\n",
       "    70.0     &         22.3        & 17.33853719500638  &  0.29718976150769855  & 16.75247379107991  & 17.92460059893285  &  10.885740703615474 &  23.791333686397287 &   4.961462804993619   & 3.2450762047448465 &   1.5289202755051259  &  0.009802967696657618   \\\\\n",
       "    71.0     &         18.3        & 16.497138659341932 &   0.2696530557370028  & 15.965378120477245 & 17.02889919820662  &  10.049047351320727 &  22.945229967363137 &   1.802861340658069   & 3.247480339967883  &   0.5551569684563198  & 0.0010624762394747629   \\\\\n",
       "    72.0     &         12.4        & 12.252116668673265 &   0.2512672606662047  & 11.756613239032063 & 12.747620098314467 &  5.806914119903279  &  18.69731921744325  &  0.14788333132673515  &  3.24895461535915  &  0.04551720440403494  & 6.1959183510719195e-06  \\\\\n",
       "    73.0     &         8.8         & 8.306575512732625  &  0.39719371708069423  & 7.5233025605636845 & 9.089848464901566  &  1.8328880964694356 &  14.780262928995814 &  0.49342448726737587  & 3.234359052433394  &  0.15255711541863118  & 0.00017549438315144227  \\\\\n",
       "    74.0     &         11.0        & 13.183834821160453 &  0.23526052824036658  & 12.719896947626015 & 13.64777269469489  &  6.740982145801145  &  19.62668749651976  &  -2.1838348211604526  & 3.250152890680419  &  -0.6719175665312369  &  0.001182748888177972   \\\\\n",
       "    75.0     &         17.0        & 17.176912617534114 &   0.2914986113751585  & 16.60207226113799  & 17.751752973930238 &  10.725125757971366 &  23.628699477096863 &  -0.17691261753411425 & 3.245592378674897  &  -0.05450857559825296 & 1.1983528185319118e-05  \\\\\n",
       "    76.0     &         8.7         &  7.83596277244573  &   0.419175232041962   & 7.009341888583902  & 8.662583656307557  &  1.3568876585485743 &  14.315037886342886 &   0.8640372275542694  & 3.2315837377033554 &  0.26737268710490836  & 0.0006014014692243932   \\\\\n",
       "    77.0     &         6.9         & 8.339851161035739  &   0.3956611236279878  & 7.559600509941949  & 9.120101812129528  &  1.8665287278166725 &  14.813173594254806 &  -1.4398511610357385  & 3.2345468931823604 &  -0.44514771576525763 & 0.0014825118013199353   \\\\\n",
       "    78.0     &         14.2        & 12.760758721306578 &  0.24123509673811552  & 12.285038894272063 & 13.236478548341093 &  6.317046933856841  &  19.204470508756316 &   1.4392412786934212  & 3.249714903964342  &   0.4428823208268775  & 0.0005404271433223485   \\\\\n",
       "    79.0     &         5.3         & 7.289291407466003  &   0.4453478594542656  & 6.411057644906277  & 8.167525170025728  &  0.8034293377342738 &  13.775153477197732 &  -1.9892914074660029  & 3.2280809489580222 &  -0.6162458249716809  & 0.0036139978447241373   \\\\\n",
       "    80.0     &         11.0        & 12.546843839357988 &  0.24509248698703084  & 12.063517171333787 & 13.03017050738219  &  6.102565996658443  &  18.991121682057532 &  -1.5468438393579884  & 3.249426257321242  &  -0.47603598816031406 & 0.0006446087607764029   \\\\\n",
       "    81.0     &         11.8        & 10.664392878210405 &   0.2986993047482193  & 10.075352628630084 & 11.253433127790727 &  4.211325339317714  &  17.117460417103096 &   1.1356071217895956  & 3.2449376040671645 &  0.34996269893332915  & 0.0005188827602131547   \\\\\n",
       "    82.0     &         12.3        & 18.431879924965834 &   0.3396783570305652  & 17.76202826805966  & 19.10173158187201  &  11.97093467770171  &  24.89282517222996  &   -6.131879924965833  & 3.2409041859813192 &  -1.8920275247536051  &  0.019662026337524154   \\\\\n",
       "    83.0     &         11.3        & 10.612102573734084 &  0.30059130004127904  & 10.01933127636787  & 11.204873871100299 &  4.158693392776614  &  17.065511754691556 &   0.6878974262659163  & 3.2447628879913113 &  0.21200237120924517  & 0.0001928582947962124   \\\\\n",
       "    84.0     &         13.6        & 10.284099754746247 &   0.3128371875663688  & 9.667179353148967  & 10.901020156343527 &  3.8284275954903357 &  16.73977191400216  &   3.3159002452537525  & 3.243605127481116  &   1.0222885076731822  &  0.004860688060940899   \\\\\n",
       "    85.0     &         21.7        & 17.181666281577414 &  0.29166348775082296  & 16.606500786086798 & 17.75683177706803  &  10.72985044469181  &  23.633482118463018 &   4.518333718422586   & 3.2455775662983695 &   1.392150896450709   &  0.007825692360253335   \\\\\n",
       "    86.0     &         15.2        & 16.216672480787114 &   0.2617590214476864  & 15.700479115511579 & 16.732865846062648 &  9.769846297599031  &  22.663498663975197 &  -1.0166724807871148  & 3.2481261588240335 &  -0.3130027686963968  & 0.0003181294695379972   \\\\\n",
       "    87.0     &         12.0        & 10.659639214167104 &   0.2988705881279569  & 10.070261190768278 & 11.24901723756593  &   4.20654083429171  &   17.1127375940425  &   1.340360785832896   & 3.2449218327254465 &  0.41306412139583404  & 0.0007237070938355986   \\\\\n",
       "    88.0     &         16.0        & 12.294899645062983 &  0.25031140273964453  & 11.801281183959285 & 12.788518106166682 &  5.849841737563058  &  18.73995755256291  &   3.7051003549370165  & 3.249028397937564  &   1.140371797700802   & 0.0038593769118553827   \\\\\n",
       "    89.0     &         12.9        & 11.23007889936334  &  0.27941895990675775  & 10.679059826789045 & 11.781097971937635 &  4.780370823471411  &  17.67978697525527  &   1.6699211006366603  & 3.2466546434431316 &   0.5143513197528399  & 0.0009797815950864928   \\\\\n",
       "    90.0     &         16.7        & 12.252116668673265 &   0.2512672606662047  & 11.756613239032063 & 12.747620098314467 &  5.806914119903279  &  18.69731921744325  &   4.447883331326734   &  3.24895461535915  &   1.3690198411205108  &  0.005604979258321018   \\\\\n",
       "    91.0     &         11.2        & 13.41676435928225  &  0.23295852018606372  & 12.957366085865013 & 13.876162632699488 &  6.974236981032029  &  19.859291737532473 &  -2.2167643592822515  & 3.250318700807498  &  -0.6820144617607886  &  0.001194709938312947   \\\\\n",
       "    92.0     &         7.3         & 8.392141465512061  &   0.3932589196818065  & 7.616628002585463  &  9.16765492843866  &  1.9193883127133748 &  14.864894618310748 &  -1.0921414655120616  & 3.234839833907843  &  -0.3376184051105559  & 0.0008423136354668727   \\\\\n",
       "    93.0     &         19.4        & 17.381320171396098 &  0.29872498806679837  & 16.79222927386265  & 17.970411068929547 &  10.928248009127827 &  23.83439233366437  &   2.0186798286039007  & 3.2449352397930395 &   0.6221017306751093  &  0.001639924524301346   \\\\\n",
       "    94.0     &         22.2        & 18.959536633772355 &  0.36218886330777356  & 18.245293865052634 & 19.673779402492077 &  12.493838297277422 &  25.42523497026729  &   3.240463366227644   & 3.238465771973211  &   1.0006168335239856  &  0.006261770931113387   \\\\\n",
       "    95.0     &         11.5        & 12.13802873163402  &  0.25391154610652766  & 11.63731072488812  & 12.638746738379918 &  5.6924231923410264 &  18.583634270927014 &  -0.6380287316340194  & 3.248749029349607  &  -0.1963921268986886  & 0.00011780147431573857  \\\\\n",
       "    96.0     &         16.9        & 14.795326931839824 &  0.23453702694117107  & 14.332815815512635 & 15.257838048167013 &  8.352576837461559  &  21.23807702621809  &   2.1046730681601744  & 3.250205179975538  &   0.6475508319065614  &  0.001091739467062788   \\\\\n",
       "    97.0     &         11.7        &  16.4258336986924  &   0.267578902373186   & 15.898163426512868 & 16.95350397087193  &  9.978078417819301  &   22.8735889795655  &   -4.725833698692401  &  3.24765189944227  &   -1.455154014352334  &  0.007187083945269215   \\\\\n",
       "    98.0     &         15.5        & 15.82211836519305  &   0.2519317314441481  & 15.325304587564235 & 16.318932142821865 &  9.376814945219191  &  22.26742178516691  &  -0.3221183651930506  & 3.248903158242451  &  -0.09914680416861238 & 2.955423039734522e-05   \\\\\n",
       "    99.0     &         25.4        & 20.80395828257352  &  0.44768710083095853  & 19.921111495134085 & 21.68680507001296  &  14.317469964848971 &  27.290446600298072 &   4.596041717426477   & 3.2277573621162716 &   1.423911775826016   &  0.019502198364147585   \\\\\n",
       "   100.0     &         17.2        & 13.459547335671967 &  0.23261446703180713  & 13.000827541088228 & 13.918267130255707 &  7.017068302269696  &  19.90202636907424  &   3.740452664328032   & 3.2503433416600362 &   1.1507869388400318  &  0.003391367214284665   \\\\\n",
       "   101.0     &         11.7        & 17.60474238143129  &   0.3069279761329415  & 16.999475048060944 & 18.210009714801636 &  11.150173395764611 &  24.05931136709797  &   -5.904742381431291  & 3.2441696235574917 &  -1.8201090160496194  &  0.014826227186033991   \\\\\n",
       "   102.0     &         23.8        & 21.122453773474753 &  0.46323597170552633  & 20.208944340910087 & 22.03596320603942  &  14.631721015975831 &  27.613186530973675 &   2.677546226525248   & 3.225562549922766  &   0.8301020938469662  & 0.0071060235003479735   \\\\\n",
       "   103.0     &         14.8        & 20.352360198459834 &   0.4259751671889789  & 19.51232972363995  & 21.192390673279718 &  13.871560599296853 &  26.833159797622816 &   -5.552360198459834  & 3.230694427810303  &  -1.7186274723676378  &  0.025674991154379306   \\\\\n",
       "   104.0     &         14.7        & 15.96472828649211  &  0.25530205176981385  & 15.461268178275182 & 16.468188394709035 &  9.518909151079548  &  22.41054742190467  &  -1.2647282864921099  & 3.248640052592522  &  -0.3893100700654155  & 0.0004680224661052875   \\\\\n",
       "   105.0     &         20.7        & 18.355821300273004 &  0.33652800943251765  & 17.69218218389143  & 19.019460416654578 &  11.895517195768583 &  24.816125404777424 &   2.3441786997269958  & 3.241232825301757  &   0.7232367515927383  & 0.0028193757136274296   \\\\\n",
       "   106.0     &         19.2        & 13.587896264841122 &  0.23173111866071008  & 13.130918448684202 & 14.044874080998042 &  7.145541030119547  &  20.030251499562695 &   5.612103735158877   & 3.2504064388304545 &   1.7265852258089291  &  0.007575990513088951   \\\\\n",
       "   107.0     &         7.2         &  8.22100955995319  &  0.40114839020725046  &  7.42993792325956  &  9.01208119664682  &  1.746373926941394  &  14.695645192964985 &  -1.0210095599531899  & 3.233870946401596  &  -0.3157236565328283  & 0.0007669181049413794   \\\\\n",
       "   108.0     &         8.7         & 11.329905844272682 &   0.2762621852284508  & 10.785111986537592 & 11.874699702007772 &  4.880726625696816  &  17.779085062848548 &   -2.629905844272683  & 3.246924781075013  &  -0.8099682073330803  &  0.00237467608773187    \\\\\n",
       "   109.0     &         5.3         & 7.655323538800254  &  0.42775313731933673  &  6.81178687580824  & 8.498860201792269  &  1.1740685409085154 &  14.136578536691992 &  -2.3553235388002545  & 3.2304595002042182 &  -0.7290986123340533  & 0.0046601549075276005   \\\\\n",
       "   110.0     &         19.8        & 19.173451515720945 &   0.3716101895091366  & 18.440629727067762 & 19.90627330437413  &  12.705674461754894 &  25.641228569686994 &   0.6265484842790556  & 3.2373982139982727 &  0.19353457401993548  & 0.00024675735600242774  \\\\\n",
       "   111.0     &         13.4        & 17.766366958903557 &   0.3130465551754385  &  17.1490336807219  & 18.383700237085215 &  11.310655331032045 &  24.22207858677507  &   -4.366366958903557  & 3.243584927705611  &  -1.3461546579550052  &  0.008439704321706164   \\\\\n",
       "   112.0     &         21.8        & 18.522199541788574 &   0.3434519494556111  & 17.844906294665986 & 19.19949278891116  &  12.060478533536763 &  24.983920550040384 &   3.277800458211427   & 3.2405064553802947 &   1.0115086957377333  &  0.00574665910602534    \\\\\n",
       "   113.0     &         14.1        & 15.384781273209267 &   0.2429805620236318  & 14.905619358124762 & 15.863943188293772 &  8.940814452472805  &  21.828748093945727 &  -1.2847812732092674  & 3.249584862013131  &  -0.39536781704889534 & 0.0004369783622737221   \\\\\n",
       "   114.0     &         15.9        & 16.99627338388864  &   0.2853507333557592  & 16.433556750398363 & 17.558990017378914 &  10.545555419546098 &  23.44699134823118  &  -1.0962733838886383  &  3.2461386735504   &  -0.3377161280326977  & 0.0004406537350842214   \\\\\n",
       "   115.0     &         14.6        & 10.749958830989842 &  0.29564110853614506  & 10.166949397790376 & 11.332968264189308 &  4.297438994128858  &  17.202478667850826 &   3.850041169010158   & 3.2452176604797622 &   1.1863737880808218  &  0.005840567835794737   \\\\\n",
       "   116.0     &         12.6        & 10.60259524564748  &   0.3009371485063063  & 10.00914192906355  & 11.196048562231411 &  4.149123382777898  &  17.056067108517063 &   1.9974047543525195  & 3.244730830376399  &   0.6155841142979539  & 0.0016298178301410236   \\\\\n",
       "   117.0     &         12.2        & 13.649693897404045 &  0.23138596005773326  & 13.19339674004482  & 14.10599105476327  &  7.207386908312402  &  20.09200088649569  &   -1.449693897404046  & 3.250431027792219  &  -0.44600051039652966 & 0.0005040026416075556   \\\\\n",
       "   118.0     &         9.4         & 10.664392878210405 &   0.2986993047482193  & 10.075352628630084 & 11.253433127790727 &  4.211325339317714  &  17.117460417103096 &  -1.2643928782104048  & 3.2449376040671645 &  -0.3896509062687771  & 0.0006432460212329658   \\\\\n",
       "   119.0     &         15.9        & 13.00794925155828  &  0.23746948230624682  & 12.539655281998193 & 13.476243221118366 &  6.564781436902877  &  19.451117066213683 &   2.8920507484417204  & 3.2499922421321905 &   0.8898638928886676  &  0.002113820654067064   \\\\\n",
       "   120.0     &         6.6         & 7.954804373528279  &   0.4135726956377144  & 7.1392317893758275 &  8.77037695768073  &  1.4771295680208247 &  14.432479179035733 &   -1.354804373528279  & 3.232305516867051  &  -0.41914490027583734 &  0.001438060930857408   \\\\\n",
       "   121.0     &         15.5        & 13.74952084231339  &   0.2309392435885814  & 13.294104617638967 & 14.204937066987812 &  7.307276188189981  &  20.191765496436798 &   1.7504791576866108  & 3.2504627970055213 &   0.5385322850946747  & 0.0007319789160448721   \\\\\n",
       "   122.0     &         7.0         & 7.926282389268467  &   0.4149142584172228  & 7.108064219867214  &  8.74450055866972  &  1.448273959309204  &  14.404290819227729 &  -0.9262823892684668  & 3.232133581259956  &  -0.28658542909212986 & 0.0006767314059286899   \\\\\n",
       "   123.0     &         11.6        & 17.680801006124124 &   0.3097887106366884  & 17.069892254312947 &  18.2917097579353  &  11.225700561597762 &  24.135901450650486 &   -6.080801006124124  &  3.24389769932843  &  -1.8745353798866735  &  0.016023381116020145   \\\\\n",
       "   124.0     &         15.2        & 12.884353986432428 &  0.23925744573855715  &  12.4125341217341  & 13.356173851130757 &  6.440928947634438  &  19.32777902523042  &   2.315646013567571   & 3.2498611052789443 &   0.7125369172873661  &  0.001375897460036264   \\\\\n",
       "   125.0     &         19.7        & 17.94225252850573  &  0.31986934140182155  & 17.31146459663812  & 18.57304046037334  &  11.485240397428791 &  24.39926465958267  &   1.7577474714942696  & 3.2429191993291147 &   0.5420262928098569  & 0.0014291693335091481   \\\\\n",
       "   126.0     &         10.6        & 11.17778859488702  &   0.2811036882179408  & 10.62344720863767  & 11.732129981136369 &  4.727795833775285  &  17.627781355998753 &  -0.5777885948870196  & 3.2465092091993966 &  -0.17797226425533683 & 0.00011873382676060585  \\\\\n",
       "   127.0     &         6.6         & 7.403379344505249  &   0.4398346107966961  & 6.536017804657895  & 8.270740884352604  &  0.9189805067800974 &  13.887778182230402 &  -0.8033793445052497  & 3.2288367633083497 &  -0.24881386189436422 &  0.000574388547403893   \\\\\n",
       "   128.0     &         8.8         & 10.84503211185588  &  0.29229970582109843  & 10.268611983210969 & 11.421452240500793 &   4.39310430610728  &  17.296959917604482 &   -2.04503211185588   & 3.2455203297658017 &  -0.6301091671188054  & 0.0016102365827143014   \\\\\n",
       "   129.0     &         24.7        & 17.50491543652195  &  0.30322506099398167  & 16.906950316524572 & 18.10288055651933  &  11.05102711004632  &  23.958803762997583 &   7.195084563478048   & 3.2445178210839614 &   2.217612896659708   &  0.021476887282717513   \\\\\n",
       "   130.0     &         9.7         & 9.865777318935674  &   0.3293141180417067  & 9.216364122459973  & 10.515190515411375 &  3.4069190803890406 &  16.324635557482306 &  -0.1657773189356746  & 3.2419737106590847 &  -0.05113468946112228 & 1.3489721137701748e-05  \\\\\n",
       "   131.0     &         1.6         &  7.06586919743081  &  0.45621641001737673  & 6.166202463201908  & 7.965535931659711  &  0.5770701961854305 &  13.55466819867619  &   -5.465869197430809  & 3.226562864129115  &  -1.6940222235236404  &  0.02868598418321617    \\\\\n",
       "   132.0     &         12.7        & 19.639310591964538 &   0.3926377721902124  & 18.865022042747675 &  20.4135991411814  &  13.16670408427899  &  26.111917099650086 &   -6.939310591964539  & 3.234915286185363  &  -2.1451289996986067  &  0.03389496283084112    \\\\\n",
       "   133.0     &         5.7         & 7.431901328765061  &   0.4384603265392408  & 6.5672499014929215 & 8.296552756037201  &  0.9478644429532075 &  13.915938214576915 &   -1.731901328765061  & 3.2290236714829645 &  -0.5363544851220203  &  0.002652112765811709   \\\\\n",
       "   134.0     &         19.6        & 17.48114711630544  &   0.3023522937331588  & 16.884903108600483 & 18.077391124010397 &  11.027418026654326 &  23.934876205956556 &   2.1188528836945615  & 3.2445992694661876 &   0.6530399311971621  & 0.0018516286116830177   \\\\\n",
       "   135.0     &         10.8        & 8.786695581106125  &   0.3753899958416502  & 8.046419948302397  & 9.526971213909853  &   2.31806974106808  &  15.25532142114417  &   2.013304418893876   & 3.2369621066623915 &   0.621973428341977   & 0.0026013801693335024   \\\\\n",
       "   136.0     &         11.6        &  9.32861328204255  &   0.3516797177560902  & 8.635094732027849  & 10.022131832057251 &  2.8651714570471842 &  15.792055107037916 &   2.2713867179574496  & 3.239623852404044  &   0.7011266805780277  & 0.0028964661736946835   \\\\\n",
       "   137.0     &         9.5         & 8.249531544213001  &  0.39982799376203065  & 7.461063752387014  & 9.037999336038988  &  1.7752135334390573 &  14.723849554986945 &   1.250468455786999   & 3.234034462455595  &  0.38665897667569105  &  0.001142571290380754   \\\\\n",
       "   138.0     &         20.8        & 20.043372035645206 &   0.4113745472250223  & 19.232134238581455 & 20.854609832708956 &  13.566241574610029 &  26.520502496680383 &   0.7566279643547951  & 3.232586009813448  &  0.23406274792312795  & 0.00044361810227685675  \\\\\n",
       "   139.0     &         9.6         & 9.076669087747545  &  0.36257304039261995  & 8.361668715101924  & 9.791669460393166  &  2.6108870175901915 &   15.5424511579049  &   0.5233309122524545  & 3.2384227826716314 &  0.16160055291505743  & 0.00016367396887917625  \\\\\n",
       "   140.0     &         20.7        & 15.82211836519305  &   0.2519317314441481  & 15.325304587564235 & 16.318932142821865 &  9.376814945219191  &  22.26742178516691  &   4.877881634806949   & 3.248903158242451  &   1.5013933617663509  &  0.006777213969135401   \\\\\n",
       "   141.0     &         10.9        & 10.521782956911347 &   0.3038994420474418  & 9.922487945689822  & 11.121077968132871 &  4.067771277625359  &  16.975794636197335 &   0.3782170430886538  & 3.2444547243056845 &   0.1165733768005015  & 5.961356957799329e-05   \\\\\n",
       "   142.0     &         19.2        & 16.240440801003622 &   0.2623999737711761  & 15.722983466543708 & 16.757898135463538 &  9.793513289477586  &  22.687368312529657 &   2.959559198996377   & 3.248074442298253  &   0.911173451093156   & 0.0027092416581900197   \\\\\n",
       "   143.0     &         20.1        & 17.514422764608554 &   0.3035751346237533  & 16.915767293294735 & 18.113078235922373 &  11.060470439155653 &  23.968375090061457 &   2.5855772353914475  & 3.244485084968706  &   0.796914508058645   &  0.002779932811581932   \\\\\n",
       "   144.0     &         10.4        & 12.004926138421563 &   0.2571671730367672  & 11.497787978467924 & 12.512064298375202 &  5.558818680492702  &  18.451033596350424 &   -1.604926138421563  & 3.2484929388962045 &  -0.4940525248507685  & 0.0007648626572711786   \\\\\n",
       "   145.0     &         11.4        & 11.605618358784197 &  0.26796954950758806  & 11.077177723627958 & 12.134058993940435 &   5.15779998736823  &  18.053436730200165 &  -0.20561835878419643 &  3.24761968978557  &  -0.06331355836735082 & 1.3645957367980035e-05  \\\\\n",
       "   146.0     &         10.3        & 13.70198420188037  &  0.23113484749545737  & 13.246182242882856 & 14.157786160877883 &  7.2597122678720805 &  20.14425613588866  &   -3.401984201880369  & 3.2504488938021274 &  -1.0466198094568369  & 0.0027694407378722552   \\\\\n",
       "   147.0     &         13.2        & 18.44614091709574  &  0.34027186356043454  & 17.775118854939453 & 19.117162979252026 &  11.985074220815209 &  24.907207613376272 &   -5.24614091709574   & 3.2408419257679526 &  -1.6187586550839288  &  0.014443438395588919   \\\\\n",
       "   148.0     &         25.4        &  18.5935045024381  &   0.3464553525595856  & 17.910288491901493 & 19.27672051297471  &  12.131160008143597 &  25.055848996732607 &   6.806495497561897   & 3.240186725734959  &   2.1006491519460213  &  0.025225020290373754   \\\\\n",
       "   149.0     &         10.9        & 8.838985885582447  &  0.37305792076713873  & 8.103309145585277  & 9.574662625579618  &  2.3708847336478396 &  15.307087037517055 &   2.061014114417553   & 3.2372317057478477 &   0.6366594367521273  & 0.0026914686524173803   \\\\\n",
       "   150.0     &         10.1        & 9.157481376483679  &  0.35905326222825923  & 8.449422067896274  & 9.865540685071084  &  2.6924631839058577 &   15.6224995690615  &   0.942518623516321   & 3.2388149196626634 &  0.29100725015015316  & 0.0005203830162551537   \\\\\n",
       "   151.0     &         16.1        & 20.376128518676342 &  0.42710728034059214  & 19.53386549693459  & 21.218391540418093 &  13.895039162427775 &  26.85721787492491  &   -4.276128518676341  & 3.2305449540327222 &  -1.3236554759401833  &  0.015312365846202767   \\\\\n",
       "   152.0     &         11.6        & 12.784527041523088 &  0.24084026000728037  & 12.30958583942267  & 13.259468243623505 &  6.340872690819792  &  19.228181392226382 &  -1.1845270415230882  & 3.2497441896410626 &  -0.36449854893160694 & 0.00036485595141336186  \\\\\n",
       "   153.0     &         16.6        &  16.4258336986924  &   0.267578902373186   & 15.898163426512868 & 16.95350397087193  &  9.978078417819301  &   22.8735889795655  &   0.1741663013076007  &  3.24765189944227  &  0.05362837727082476  &  9.76166963855993e-06   \\\\\n",
       "   154.0     &         19.0        & 15.175620055303982 &  0.23948703649903916  & 14.703347433613233 & 15.647892676994731 &  8.732161847549115  &  21.61907826305885  &   3.824379944696018   & 3.249844194464579  &   1.1767887061201392  &  0.003760156552228026   \\\\\n",
       "   155.0     &         15.6        & 15.959974622448808 &   0.2551863114349744  & 15.456742756195075 & 16.463206488702543 &  9.514173310191492  &  22.405775934706124 &  -0.3599746224488083  & 3.248649146245626  &  -0.11080747912245956 & 3.7880637794436625e-05  \\\\\n",
       "   156.0     &         3.2         & 7.227493774903077  &   0.4483447287188032  & 6.3433501337749005 & 8.111637416031254  &  0.740828821012494  &  13.71415872879366  &   -4.027493774903077  & 3.227666081424205  &  -1.2478037297854392  &  0.015021368578435298   \\\\\n",
       "   157.0     &         15.3        & 11.496284085788252 &   0.2711809106498307  & 10.961510590331875 & 12.03105758124463  &  5.047943606461222  &  17.944624565115284 &   3.8037159142117485  & 3.2473531133286615 &   1.171328088281965   &  0.004783946538392604   \\\\\n",
       "   158.0     &         10.1        & 14.153582285994057 &  0.23054121841672584  & 13.698950973915151 & 14.608213598072963 &   7.71139307146399  &  20.595771500524123 &   -4.053582285994057  & 3.250491051450096  &  -1.2470676651103805  &  0.003911553370696411   \\\\\n",
       "   159.0     &         7.3         & 7.588772242194027  &  0.43093152660356654  & 6.738967739982152  & 8.438576744405903  &  1.1066985047343474 &  14.070845979653708 &  -0.2887722421940273  & 3.2300370506118563 &  -0.08940214544577005 & 7.113239215323387e-05   \\\\\n",
       "   160.0     &         12.9        & 13.293169094156397 &  0.23409036278291606  & 12.83153880735601  & 13.754799380956785 &   6.85048217272553  &  19.735856015587263 &  -0.3931690941563968  & 3.250237380715197  &  -0.12096627049125934 & 3.7952072274045525e-05  \\\\\n",
       "   161.0     &         14.4        & 15.232664023823604 &  0.24038703544473072  & 14.75861658848192  & 15.70671145916529  &  8.789075488167486  &  21.67625255947972  &  -0.8326640238236038  & 3.2497777465753432 &  -0.2562218369244099  & 0.0001796044312556081   \\\\\n",
       "   162.0     &         13.3        & 11.10648363423749  &   0.2834347148315913  & 10.547545422764726 & 11.665421845710254 &  4.656094175442828  &  17.556873093032152 &   2.1935163657625107  & 3.2463065307168013 &   0.675696008681648   & 0.0017402023184303506   \\\\\n",
       "   163.0     &         14.9        & 15.988496606708619 &   0.2558842119366363  & 15.48388846846782  & 16.49310474494942  &  9.542587701126429  &  22.43440551229081  &  -1.0884966067086186  & 3.248594249675971  &  -0.33506696221517657 & 0.00034828058068680644  \\\\\n",
       "   164.0     &         18.0        & 14.804834259926427 &  0.23463798538373948  & 14.342124051785959 & 15.267544468066895 &  8.362069870116542  &  21.24759864973631  &   3.1951657400735733  & 3.2501978931691653 &   0.9830680608060046  & 0.0025183391117498777   \\\\\n",
       "   165.0     &         11.9        & 12.603887807877612 &   0.2440110746316296  & 12.122693703919008 & 13.085081911836216 &  6.159769558530425  &   19.0480060572248  &  -0.7038878078776118  & 3.2495076433828154 &  -0.21661367970959677 & 0.0001322896031844715   \\\\\n",
       "   166.0     &         11.9        & 18.17993573067083  &  0.32934295319774803  & 17.53046567076344  & 18.82940579057822  &  11.721071774478453 &  24.63879968686321  &  -6.2799357306708306  & 3.2419707815039307 &  -1.9370735129690486  &  0.019361578793655417   \\\\\n",
       "   167.0     &         8.0         & 7.8834994128787494 &  0.41693022902485655  & 7.061305714204443  & 8.705693111553055  &  1.404987645194395  &  14.362011180563105 &  0.11650058712125055  & 3.231874148705593  &  0.03604737739181785  & 1.0812727001237347e-05  \\\\\n",
       "   168.0     &         12.2        & 16.863170790676183 &  0.28097275334880883  & 16.30908761027722  & 17.417253971075144 &  10.413200215806405 &  23.31314136554596  &   -4.663170790676183  & 3.2465205437239746 &  -1.4363595510556102  &  0.007726600205101863   \\\\\n",
       "   169.0     &         17.1        & 17.271985898400153 &   0.2948252755361554  & 16.69058530213566  & 17.853386494664647 &  10.819611227070098 &  23.72436056973021  &  -0.17198589840015188 & 3.245291879916389  &  -0.05299551003855557 & 1.1589642955285877e-05  \\\\\n",
       "   170.0     &         15.0        & 20.547260424235215 &   0.4352943144091079  & 19.68885242821873  &  21.4056684202517  &  14.064053152096683 &  27.030467696373748 &  -5.5472604242352155  & 3.2294519951207397 &  -1.7177095162325893  &  0.026802652178146695   \\\\\n",
       "   171.0     &         8.4         & 9.409425570778684  &  0.34823715018971363  &  8.7226958241735   & 10.096155317383866 &  2.9467086505695557 &  15.872142490987812 &  -1.0094255707786832  & 3.239995712369689  &  -0.31155151438160483 & 0.0005606490192495998   \\\\\n",
       "   172.0     &         14.5        & 14.852370900359446 &  0.23516059899155817  & 14.388630089050206 & 15.316111711668686 &  8.409532412087474  &  21.29520938863142  &  -0.3523709003594462  & 3.250160122459839  &  -0.10841647398367535 &  3.07666465400424e-05   \\\\\n",
       "   173.0     &         7.6         & 7.964311701614883  &  0.41312594180082135  & 7.1496201238370745 & 8.779003279392692  &  1.4867477603799513 &  14.441875642849816 &  -0.36431170161488335 & 3.2323626475315863 &  -0.11270755832211223 & 0.00010375304748821606  \\\\\n",
       "   174.0     &         11.7        & 15.037763798048225 &  0.23747924507498622  & 14.569450576137553 & 15.506077019958896 &  8.594594584089826  &  21.480933012006624 &  -3.3377637980482255  & 3.249991528774319  &  -1.0270069224786589  & 0.0028158116901326876   \\\\\n",
       "   175.0     &         11.5        & 17.60474238143129  &   0.3069279761329415  & 16.999475048060944 & 18.210009714801636 &  11.150173395764611 &  24.05931136709797  &   -6.10474238143129   & 3.2441696235574917 &  -1.8817580736536677  &  0.015847597222093227   \\\\\n",
       "   176.0     &         27.0        & 20.195489285030867 &   0.4185348707812062  & 19.370131204767375 & 21.020847365294358 &  13.716575162545436 &  26.674403407516298 &   6.804510714969133   & 3.231666735739683  &   2.105573151995104   &  0.03718097998091955    \\\\\n",
       "   177.0     &         20.2        & 18.840695032689805 &  0.35702479736972564  &  18.1366358922566  & 19.54475417312301  &  12.376113722263547 &  25.305276343116063 &   1.3593049673101945  & 3.2390391512004495 &  0.41966302469867034  & 0.0010698817637108406   \\\\\n",
       "   178.0     &         11.7        & 15.12332975082766  &   0.2386974247957469  & 14.652614257216506 & 15.594045244438814 &  8.679985485478298  &  21.56667401617702  &  -3.4233297508276603  & 3.2499022859683184 &  -1.0533639013111649  & 0.0029928277837426016   \\\\\n",
       "   179.0     &         11.8        & 20.185981956944264 &   0.4180857486119499  & 19.36150955344823  &  21.0104543604403  &  13.707180602526037 &  26.66478331136249  &   -8.385981956944264  & 3.2317248700583727 &  -2.5948935302753022  &  0.05634703364231869    \\\\\n",
       "   180.0     &         12.6        & 14.904661204835769 &  0.23576960300761832  & 14.439719426962787 & 15.36960298270875  &  8.461736162380546  &  21.34758624729099  &   -2.304661204835769  & 3.2501160015057695 &  -0.7091012147775729  & 0.0013230137681933584   \\\\\n",
       "   181.0     &         10.5        & 14.476831440938591 &  0.23185230743654558  & 14.019614638397606 & 14.934048243479577 &  8.034459249702607  &  20.919203632174575 &   -3.976831440938591  & 3.250397796652368  &   -1.223490689365587  & 0.0038082123479843324   \\\\\n",
       "   182.0     &         12.2        & 17.419349483742515 &   0.3000994445394886  &  16.8275481340224  & 18.01115083346263  &  10.96602932405607  &  23.87266964342896  &   -5.219349483742516  & 3.244808415351099  &  -1.6085231593489209  &  0.011065649362841374   \\\\\n",
       "   183.0     &         8.7         & 9.704152741463407  &   0.3359108039647808  & 9.041730765051623  & 10.36657471787519  &  3.2439735550384494 &  16.164331927888362 &  -1.0041527414634075  & 3.241296848597172  &  -0.30979968462253105 & 0.0005153974645524297   \\\\\n",
       "   184.0     &         26.2        & 20.70413133766418  &  0.44285225058129574  & 19.830818959419787 & 21.577443715908572 &  14.21893382672592  &  27.18932884860244  &    5.49586866233582   & 3.228424261633112  &   1.7023378022675717  &  0.02726452891907084    \\\\\n",
       "   185.0     &         17.6        & 19.09739289102811  &   0.3682423911529699  & 18.371212459595107 & 19.823573322461115 &  12.630364959676557 &  25.564420822379667 &  -1.4973928910281096  & 3.2377830177922924 &  -0.4624747497900951  & 0.0013833056116016916   \\\\\n",
       "   186.0     &         22.6        & 16.777604837896746 &   0.278229689933718   & 16.228931026495147 & 17.326278649298345 &  10.32809670182909  &  23.227112973964402 &   5.8223951621032555  & 3.2467567769368877 &   1.793295760083489   &  0.011808134186751541   \\\\\n",
       "   187.0     &         10.3        & 13.663954889533953 &   0.2313137462695858  & 13.207800139027094 & 14.12010964004081  &  7.221657985300579  &  20.106251793767328 &   -3.363954889533952  & 3.2504361676139637 &  -1.0349241505035673  &  0.00271210593212249    \\\\\n",
       "   188.0     &         17.3        & 16.116845535877772 &  0.25912598550638777  & 15.605844563498243 & 16.627846508257303 &  9.670433026608933  &  22.56325804514661  &   1.1831544641222287  & 3.2483372750657473 &   0.3642338722657059  & 0.0004221145948575232   \\\\\n",
       "   189.0     &         15.9        & 20.62807271297135  &  0.43918162206569866  & 19.76199887831435  & 21.494146547628347 &  14.143845994775692 &  27.112299431167006 &   -4.728072712971349  & 3.228925646679707  &  -1.4642866483572359  &  0.01983327514827168    \\\\\n",
       "   190.0     &         6.7         & 7.921528725225166  &  0.41513804106234925  & 7.102869252536487  & 8.740188197913843  &  1.4434645407555617 &  14.39959290969477  &  -1.2215287252251654  & 3.232104846042148  &  -0.3779359839520615  &  0.001178204492990001   \\\\\n",
       "   191.0     &         10.8        & 8.910290846231977  &  0.36989228808111174  & 8.180856789220053  &  9.6397249032439   &  2.4428967582384358 &  15.377684934225517 &   1.889709153768024   & 3.2375949444246945 &   0.5836768299327254  &  0.002223414525516667   \\\\\n",
       "   192.0     &         9.9         & 10.621609901820689 &  0.30024601765763503  & 10.029519507349807 & 11.21370029629157  &  4.1682632288834895 &  17.074956574757888 &  -0.7216099018206883  & 3.2447948560466733 &  -0.22238999192074305 & 0.0002117290770624013   \\\\\n",
       "   193.0     &         5.9         & 7.850223764575635  &   0.4185011793359016  &  7.02493212443114  &  8.67551540472013  &  1.3713181056562735 &  14.329129423494997 &   -1.950223764575635  & 3.231671098958042  &  -0.6034722299569494  &  0.003053680865926336   \\\\\n",
       "   194.0     &         19.6        & 14.961705173355393 &  0.23647443269852705  & 14.495373459013042 & 15.428036887697743 &   8.51867967956085  &  21.404730667149934 &   4.638294826644609   & 3.2500647949888832 &   1.427139186208278   &  0.005391219476520459   \\\\\n",
       "   195.0     &         17.3        & 14.148828621950754 &  0.23053271627215272  & 13.694214076249546 & 14.603443167651962 &  7.706640590617917  &  20.59101665328359  &   3.1511713780492467  & 3.2504916544538927 &   0.9694445373306665  &  0.002363648888386262   \\\\\n",
       "   196.0     &         7.6         &  8.84849321366905  &   0.3726348646458637  & 8.113650747737138  & 9.583335679600962  &  2.3804868983024807 &  15.31649952903562  &  -1.2484932136690503  & 3.2372804306387453 &  -0.3856611252620803  & 0.0009853444184807923   \\\\\n",
       "   197.0     &         9.7         & 11.510545077918158 &  0.27075617630292786  & 10.976609166017308 & 12.044480989819007 &  5.062274007010676  &  17.95881614882564  &  -1.8105450779181584  & 3.247388554198595  &  -0.5575387877675676  & 0.0010804592962577679   \\\\\n",
       "   198.0     &         12.8        & 15.446578905772194 &  0.24411306738888455  & 14.96518367031367  & 15.927974141230719 &  9.002445634446476  &  21.89071217709791  &   -2.646578905772193  &  3.24949998296295  &  -0.8144572763957972  & 0.0018717834254780047   \\\\\n",
       "   199.0     &         25.5        &  20.5139847759321  &    0.43369755251424   & 19.658725622280237 & 21.369243929583966 &  14.031193674424184 &  26.99677587744002  &   4.9860152240678985  & 3.229666819021643  &   1.5438172119495295  &  0.021489200634195436   \\\\\n",
       "   200.0     &         13.4        & 18.065847793631583 &   0.3247605614135507  & 17.425414290412913 & 18.706281296850253 &  11.607886248536268 &   24.5238093387269  &   -4.665847793631583  & 3.2424330227001725 &  -1.4389958901128037  &  0.010386605835451347   \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\end{center}"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.table.SimpleTable'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "st"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 12)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Obs',\n",
       " 'Dep Var\\nPopulation',\n",
       " 'Predicted\\nValue',\n",
       " 'Std Error\\nMean Predict',\n",
       " 'Mean ci\\n95% low',\n",
       " 'Mean ci\\n95% upp',\n",
       " 'Predict ci\\n95% low',\n",
       " 'Predict ci\\n95% upp',\n",
       " 'Residual',\n",
       " 'Std Error\\nResidual',\n",
       " 'Student\\nResidual',\n",
       " \"Cook's\\nD\"]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ss2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.00000000e+00,  2.21000000e+01,  1.79707745e+01, ...,\n",
       "         3.24280835e+00,  1.27334860e+00,  7.94343302e-03],\n",
       "       [ 2.00000000e+00,  1.04000000e+01,  9.14797405e+00, ...,\n",
       "         3.23876912e+00,  3.86574623e-01,  9.20433966e-04],\n",
       "       [ 3.00000000e+00,  9.30000000e+00,  7.85022376e+00, ...,\n",
       "         3.23167110e+00,  4.48615033e-01,  1.68755025e-03],\n",
       "       ...,\n",
       "       [ 1.98000000e+02,  1.28000000e+01,  1.54465789e+01, ...,\n",
       "         3.24949998e+00, -8.14457276e-01,  1.87178343e-03],\n",
       "       [ 1.99000000e+02,  2.55000000e+01,  2.05139848e+01, ...,\n",
       "         3.22966682e+00,  1.54381721e+00,  2.14892006e-02],\n",
       "       [ 2.00000000e+02,  1.34000000e+01,  1.80658478e+01, ...,\n",
       "         3.24243302e+00, -1.43899589e+00,  1.03866058e-02]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "fittedvalues = data[:, 2]\n",
    "predict_mean_se  = data[:, 3]\n",
    "predict_mean_ci_low, predict_mean_ci_upp = data[:, 4:6].T\n",
    "predict_ci_low, predict_ci_upp = data[:, 6:8].T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Disambiguation of the Confidence Interval\n",
    "\n",
    "* The 95% interval relates to the mean prediction $y$ for input $x$ \n",
    "  * I.e., the mean value for predictions of type $x$ will be in that confidence interval \n",
    "  * This is what we are after if we are interested in the average behavior\n",
    "* This is not to be confused with the 95% prediction interval of $y$\n",
    "  * I.e., we are 95% confident that the true prediction will be in that interval\n",
    "  * These are the interval we are interested in if we are after extreme cases\n",
    "  \n",
    " * See https://stats.stackexchange.com/questions/16493/difference-between-confidence-intervals-and-prediction-intervals\n",
    " and https://stackoverflow.com/questions/17559408/confidence-and-prediction-intervals-with-statsmodels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Confidence Interval (CI)\n",
    "\n",
    "The **confidence interval** for a regression model's prediction relates to the estimated mean (or expected value) of the dependent variable ($y$) for a given value of the independent variable ($x$). \n",
    "\n",
    "* This interval provides a range within which we are confident (to a certain degree, typically 95%) that the true mean of $y$ falls, given a specific $x$. \n",
    "\n",
    "  - The interval gives us a range that, based on our model, likely includes the average outcome ($y$) for a specific input ($x$).\n",
    "  - If we were to repeat our study multiple times, collecting new samples each time, and calculate a confidence interval for each sample, we would expect about 95% of those intervals to contain the true mean value of $y$ for the given $x$.\n",
    "  - It's about the average behavior or the expected outcome. If your interest lies in understanding what the typical or average response ($y$) would be for a given condition ($x$), then you look at the confidence interval.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Prediction Interval (PI)\n",
    "\n",
    "* The **prediction interval**, on the other hand, provides a range for individual observations ($y$) for a specific value of $x$, within which we expect to find the true value of a single observed response with a certain level of confidence (again, typically 95%).\n",
    "\n",
    "  - This interval is wider than the confidence interval because it accounts not only for the uncertainty of the mean estimate but also for the natural variability (or noise) in the data.\n",
    "  - When we say a 95% prediction interval, it means we are 95% confident that a new observation (a single actual outcome of $y$ for a given $x$) will fall within this range.\n",
    "  - It's useful when you're interested in the potential variation of individual outcomes, including extreme cases, rather than the average outcome.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VFYWEhARotVrk5uYyE01ERERENi880BtD29VCeLCf8Z31eq6ibWH2E0T7+AAhIYbbPRTMFd8mpq+Pj/HjekCXLl2watUquLi4oEaNGqUW2PLy8irxb71ej+DgYOzbt6/Usfz8/Co1lrI8OJ6ilQIfnrf8ILHje/hxAUC/fv2g1+uxbds2tG7dGgcPHsSSByoJPvjgA0RHR2Px4sUIDw+Hh4cHXnjhBWg0GgmPjIiIiIjICty+DdSsCQAIN6Yfy7Otiv0E0ZUptX64vNtEvLy8EB4u/uPSsmVLJCUlwdnZGWFhYWW2efTRR3H06FG8/vrrxbcdPXq0skMtxdXVFTqdzujxlcfDwwPPPfcc1q9fj9jYWDRo0ACPP/548f0HDx7EkCFD8OyzzwIonCMdHx9f2YdBRERERGReffsC27YZ12fjRmDgQNOMhyrNfoJoO9S9e3e0a9cOzzzzDD7++GM0bNgQCQkJ2L59O5555hm0atUK7777Lt544w20atUKTz75JNavX48LFy6gbt26so4lLCwM165dw+nTp1GzZk14e3uLGl9FXnnlFfTr1w8XLlzAq6++WuK+8PBwbN68Gf369YNCocD06dMrzIoTEREREVkFQQCcJKzfnJkpfq9nsiiuzm3FFAoFtm/fjo4dO2LYsGFo0KABBg0ahPj4eFSvXh1A4crZM2bMwMSJE/H444/j+vXrGDlypOxjef7559GrVy906dIFAQEB+Omnn0SNryJdu3aFv78/rly5gsGDB5e4b+nSpahSpQrat2+Pfv36ISIiAi1btpT9cRERERERVVpq6v0tqIwJoB9cTZsBtM1QCA+vq25hGRkZ8PX1hVqths9Dc5Dz8vJw7do11KlTB+7u7hYaIZF14eeCiIiIyAJ++w147jnj+gweDKxfb5rxGEmvF3A7PRfZGi28XJ0R4ucBJyfHXbCsojj0YSznJiIiIiIiMkRqmfapU0CLFvKPpxJiUzIRfT4ZcalZyNPq4O6sRL0AFSKaVEd4oLelh2f1GEQTERERERGVJTcX8PQ0vp9WC/z/1q3WJjYlE2sPxyMtW4NgX3d4unogR6PF+QQ1EtS5GNohjIG0AZwTTUREREREVOS33+7PbzYmgH5wfrOVBtB6vYDo88lIy9agfqAK3u4uUDop4O3ugvqBKqRla7DzQjL0equa8Wt1GEQTEREREZFja9bsfuAsdp7zr7+WDJxtwO30XMSlZiHY1x0KRcn5zwqFAsG+7ohNycLt9FwLjdA2sJybiIiIiIgci04HOEsIhbKzpZV3W4lsjRZ5Wh08XT3KvN/DVYnkjDxka7RmHpltYSaaiIiIiIjs39mz97PNxgTQD2abbTiABgAvV2e4OyuRU06QnKvRwc1ZCS9X5lorwiCaiIiIiIjsU69e9wPnZs3E9alXz+bKtMUK8fNAvQAVEtV5eHinY0EQkKjOQ3igCiF+ZWeqqRAvMRARERERkX2QWqZ9+rT4INuGOTkpENGkOhLUuYhJKZwb7eGqRK5Gh0R1Hvy9XNGzcXWH3i9aDAbRRERERERku1JSgOrVje9nxdtQmVJ4oDeGdggr3ic6OSMPbs5KNA3xRc/G3CdaDAbRRERERERkWwYOBDZtMr6fnZVnSxUe6I26nVW4nZ6LbI0WXq7OCPHzYAZaJM6JtkOCICAyMhL+/v5QKBQ4ffq0pYdkFkOGDMEzzzxjsN1rr72G+fPnm35AMli5ciX69+9v6WEQERERWZYg3J/brFCID6AHDrTb+c2V5eSkQKi/Jx4J8kGovycDaCMwiDajpKQkvPPOO6hbty7c3NwQGhqKfv36Yc+ePbKeZ8eOHVi3bh2ioqKQmJiIJk2aGOwTFhaGZcuWiT7Hvn37oFAokJ6eLn2gFnD27Fls27YN77zzjqWHIsrw4cNx/PhxHDp0yNJDISIiIjKvxMT7QbOTEWFLSsr9oHnjRtONjxwWy7nNJD4+Hh06dICfnx8WLVqExx57DAUFBYiOjsbo0aNx+fJl2c4VFxeH4OBgtG/fXrZjmoogCNDpdHCWsgCEBCtXrsSLL74Ib2/bmOvh5uaGwYMHY8WKFXjyySctPRwiIiIi09q5E4iIML4fs8wAAL1eYIm2GTATbSajRo2CQqHAsWPH8MILL6BBgwZo3Lgxxo8fj6NHjxa3u3HjBgYMGACVSgUfHx+89NJLSE5OLr5/5syZaN68OX744QeEhYXB19cXgwYNQmZmJoDCkuZ33nkHN27cgEKhQFhYmKTxKhQKfP3113j22Wfh6emJ+vXrY+vWrQAKLwh06dIFAFClShUoFAoMGTIEQGFQvGjRItStWxceHh5o1qwZfvnll+LjFmWwo6Oj0apVK7i5ueGbb76BQqEodSFhyZIlCAsLKw6033zzTdSpUwceHh5o2LAhli9fbtRj0uv1+Pnnn0uVR4eFhWHu3Ll4/fXXoVKpULt2bfz+++9ITU0tfi2aNm2KEydOlOh35MgRdOzYER4eHggNDcXYsWORnZ1dfP+PP/6IVq1awdvbG0FBQRg8eDBSUlJKPRd79uxBq1at4Onpifbt2+PKlSslztO/f39s2bIFubm5Rj1eIiIiIqv3cJm22AC6SROWaT8kNiUTq/bFYemuq/hsTwyW7rqKVfviEJuSaemh2R27yERnZ2fj4sWLZj1no0aN4OXlJaptWloaduzYgXnz5pXZx8/PD0BhAPrMM8/Ay8sL+/fvh1arxahRozBw4EDs27evuH1cXBy2bNmCqKgo3Lt3Dy+99BIWLlyIefPmYfny5ahXrx7WrFmD48ePQ1mJFQdnzZqFRYsW4ZNPPsGKFSvwyiuv4Pr16wgNDcWvv/6K559/HleuXIGPjw88PAr3kps2bRo2b96MVatWoX79+jhw4ABeffVVBAQEoFOnTsXH/vDDD7F48WLUrVsXfn5++Oqrr7B+/XrMmTOnuM2GDRswePBgKBQK6PV61KxZE5s2bUK1atVw5MgRREZGIjg4GC+99JKox3P27Fmkp6ejVatWpe5bunQp5s+fj+nTp2Pp0qV47bXX0KFDBwwbNgyffPIJJk6ciNdffx0XLlyAQqHAuXPnEBERgTlz5uCbb75BamoqxowZgzFjxmDt2rUAAI1Ggzlz5qBhw4ZISUnBe++9hyFDhmD79u0lzj116lR8+umnCAgIwIgRIzBs2DAcPny4+P5WrVqhoKAAx44dK/EcEhEREVWWRTKX2dmASmV8v+hooGdP+cfzAFvN5MamZGLt4XikZWsQ7OsOT1cP5Gi0OJ+gRoI6F0M7hIleddtWnwNzsosg2trFxsZCEAQ88sgjFbbbvXs3zp49i2vXriE0NBQA8MMPP6Bx48Y4fvw4WrduDaAwo7pu3brikuTXXnsNe/bswbx58+Dr6wtvb28olUoEBQVVatxDhgzByy+/DACYP38+VqxYgWPHjqFXr17w9/cHAAQGBhZfBMjOzsaSJUuwd+9etGvXDgBQt25dHDp0CKtXry4RAM6ePRs9evQo/vcrr7yClStXFgfRV69excmTJ/H9998DAFxcXDBr1qzi9nXq1MGRI0ewadMm0UF0fHw8lEolAgMDS93Xu3dvvP322wCAGTNmYNWqVWjdujVefPFFAMDEiRPRrl07JCcnIygoCJ988gkGDx6McePGAQDq16+Pzz77DJ06dcKqVavg7u6OYcOGFR+/bt26+Oyzz9CmTRtkZWVB9cAfjnnz5hU/N5MmTUKfPn2Ql5cHd3d3AICXlxf8/PwQHx/PIJqIiIhkE5uSWbzNUZ5WB3dnJeoFqBDRxATbHG3eDDz/vPH9dDrj5kNXglmfDxnp9QKizycjLVuD+oEqKBSFAa+3uwtUbs6IScnCzgvJqFtNZTAYttXnwNzsIoj28vIqDjCtkfD/JSZFb+jyXLp0CaGhocUBNFCY8fbz88OlS5eKH2NYWFiJOb3BwcElyoTl8thjjxX/fy8vL3h7e1d4nosXLyIvL69EcAwUZmRbtGhR4raHs8GDBg3CBx98gKNHj+KJJ57A+vXr0bx5czRq1Ki4zZdffomvv/4a169fR25uLjQaDZo3by768eTm5sLNza3M1+HBx1r9//cZbNq0aanbUlJSEBQUhJMnTyI2Nhbr168vbiMIAvR6Pa5du4ZHH30U//77L2bOnInTp08jLS0Ner0eQGHJ/oOP68FzBwcHF5+nVq1axbd7eHggJydH9GMlIiIiqoicmcsyCULhytg//yytr5mZ/PkwodvpuYhLzUKwr3up37kKhQLBvu6ITcnC7fRchPp7lnscW34OzM0ugmhrV79+fSgUCly6dKnCLZgEQSgzwHv4dhcXlxL3F5U7y83Y8xTdt23bNoSEhJS4z83NrcS/Hy5rDw4ORpcuXbBhwwY88cQT+Omnn4ozwwCwadMmvPfee/j000/Rrl07eHt745NPPsE///wj+vFUq1YNOTk50Gg0cHV1LfexFj3XZd1W9Bj1ej3efvttjB07ttR5atWqhezsbPTs2RM9e/bEjz/+iICAANy4cQMRERHQaDQGz/3w85yWloaAgADRj5WIiIioPHJmLkvIyQFETncs4YsvgJEjje8nE5M9H2aSrdEiT6uDp6tHmfd7uCqRnJGHbI223GPY+nNgbgyizcDf3x8RERH4/PPPMXbs2FIBZHp6Ovz8/NCoUSPcuHEDN2/eLM5GX7x4EWq1Go8++qglhl6uoiBUp9MV39aoUSO4ubnhxo0bksqOX3nlFUycOBEvv/wy4uLiMGjQoOL7Dh48iPbt22PUqFHFt8XFxRl1/KKs9cWLF43KYJelZcuWuHDhAsLDw8u8/9y5c7hz5w4WLlxY/Fo+vDCZWHFxccjLyyuVzSciIiKSQq7MJQDg+HGgTRvjB5GQAPx/BZ6lyfp8WICXqzPcnZXI0Wjh7e5S6v5cjQ5uzkp4uZYf+tn6c2BuXJ3bTL744gvodDq0adMGv/76K2JiYnDp0iV89tlnxfOHu3fvjsceewyvvPIKTp06hWPHjuH1119Hp06dylwMS6yVK1eiW7ducj0UAEDt2rWhUCgQFRWF1NRUZGVlwdvbGxMmTMB7772H7777DnFxcfj333/x+eef47vvvjN4zOeeew4ZGRkYOXIkunTpUiKbHR4ejhMnTiA6OhpXr17F9OnTcfz4caPGHBAQgJYtW8qy5/LEiRPx999/Y/To0Th9+jRiYmKwdevW4v2na9WqBVdXV6xYsQL//fcftm7dWmLRNGMcPHgQdevWRb169So9biIiIqL7mcuygyoPVyXytbryM5c9e95fTduYAPrB1bStJIAGZHg+LCzEzwP1AlRIVOcVTyMtIggCEtV5CA9UIcSv7Ew1YPvPgbkxiDaTOnXq4NSpU+jSpQvef/99NGnSBD169MCePXuwatUqAIVXebZs2YIqVaqgY8eO6N69O+rWrYv//e9/lTr3nTt3jM7aGhISEoJZs2Zh0qRJqF69OsaMGQMAmDNnDmbMmIEFCxbg0UcfRUREBP744w/UqVPH4DF9fHzQr18/nDlzBq+88kqJ+0aMGIHnnnsOAwcORNu2bXH37t0SWWmxIiMjS8xjluqxxx7D/v37ERMTg6eeegotWrTA9OnTi+c0BwQEYN26dfj555/RqFEjLFy4EIsXL5Z0rp9++gnDhw+v9JiJiIiIgJKZy7KUylxqtSW3odq1S9yJwsNtYhsqo58PK+PkpEBEk+rw93JFTEoWMvMKoNXrkZlXgJiULPh7uaJn4+oVlmHb+nNgbgrh4csVFpaRkQFfX1+o1Wr4+PiUuC8vLw/Xrl1DnTp1ilcuJjJGXl4eGjZsiI0bNxZXAFiz8+fPo1u3brh69Sp8fX3LbMPPBRERERlDrxewal8czieoS8x/BQozlzEpWWjrlochLz1p/MEvXQIM7EhjbcQ8H01DfDGiUz2rng/84Mra+drCoDc8UIWejQ2vrG0vz0FlVBSHPsyoSwkLFizA5s2bcfnyZXh4eKB9+/b4+OOP0bBhw+I2Q4YMKVW627ZtWxw9etSYUxGZhLu7O77//nvcuXPH0kMRJSEhAd9//325ATQRERGRsYoylwnqXMSkFM6D9XBVotf899H0wHbjD5ifDzy0aKstKe/5yNXokKjOE5XJtQbhgd6o21klaY9ne3kOzMWoTHSvXr0waNAgtG7dGlqtFlOnTsW5c+dw8eLF4sWyhgwZguTkZKxdu7a4n6ura/G+woYwE01kHH4uiIiISIrY5AyEB0m8UG9dxayyqEwm11448nNgskz0jh07Svx77dq1CAwMxMmTJ9GxY8fi293c3BAUFGTMoYmIiIiIyNRiY4H69QEAZe8xUo6lS4Fx40wxIqtRmUyuveBzIE6lZoar1WoAKJVl3rdvHwIDA+Hn54dOnTph3rx5CAwMLPMY+fn5yM/PL/53RkaGwfNa2TRuIovi54GIiIgqtGkTMHCg8f3UasBARs7eODkpHH4LJz4HhkkOogVBwPjx4/Hkk0+iSZMmxbc//fTTePHFF1G7dm1cu3YN06dPR9euXXHy5Em4ubmVOs6CBQswa9YsUed0cSnc9ywnJwceHuUv0U7kSHJycgDc/3wQERGRg9PrAaVSWl9enCcySPLq3KNHj8a2bdtw6NAh1KxZs9x2iYmJqF27NjZu3Ijnnnuu1P1lZaJDQ0PLrUVPTExEeno6AgMD4enpWWozcCJHIQgCcnJykJKSAj8/v+LttYiIiEgcvV6wn7LVjAxAykKkLi6ARiP/eIhsjMnmRBd55513sHXrVhw4cKDCABoAgoODUbt2bcTExJR5v5ubW5kZ6vIUzbVOSUkRP2AiO+bn58c1CIiIiIz04AJKeVod3J2VqBegQkQTG1pAadUqYNQo4/sdPw60aiX/eIgchFFBtCAIeOedd/Dbb79h3759qFOnjsE+d+/exc2bN2XLkikUCgQHByMwMBAFBQWyHJPIVrm4uEAptVyLiIjIQcWmZGLt4XikZWsQ7OsOT1cP5Gi0OJ+gRoI6F0M7hFlnIC0IQNeuwL59xvfVaqWXeBNRCUYF0aNHj8aGDRvw+++/w9vbG0lJSQAAX19feHh4ICsrCzNnzsTzzz+P4OBgxMfHY8qUKahWrRqeffZZWQeuVCoZPBARERGRUfR6AdHnk5GWrUH9QFXx1EBvdxeo3JwRk5KFnReSUbeayjpKu+/dA0RuFVsK5zcTmYSTMY1XrVoFtVqNzp07Izg4uPi///3vfwAKA9tz585hwIABaNCgAd544w00aNAAf//9N7y9rfBqHhERERE5lNvpuYhLzUKwr3uptXUUCgWCfd0Rm5KF2+m5FhohgIMHAYWi8D9jAuinnioMnIv+IyKTMLqcuyIeHh6Ijo6u1ICIiIiIiEwlW6NFnlYHT9eyd3rxcFUiOSMP2Rqt+QYlCEBICJCYaHzfW7cK+5LDsKsF8WxUpfaJJiIiIiKyJV6uznB3ViJHo4W3e+ntIXM1Org5K+HlauKfyfn5gLu7tL7MMjssu1gQzw4YVc5NRERERGTLQvw8UC9AhUR1XqkqS0EQkKjOQ3igCiF+ZWeqK2Xv3vtl2sYE0Eoly7SpeEG88wlq+Hm6oG41Ffw8XXA+QY21h+MRm5Jp6SE6DAbRREREROQwnJwUiGhSHf5erohJyUJmXgG0ej0y8woQk5IFfy9X9GxcXb7y2GeeuR84d+smvt/27feDZq0ZS8vJKj28IJ63uwuUTgp4u7ugfqAKadka7LyQDL2eF1nMgeXcRERERORQwgO9MbRDWHFZbHJGHtyclWga4ouejStZFluZMm29vjDYJsnsdb6wMQvihfp7WmiUjoNBNBERERE5nPBAb9TtrJIn4IqPB+rUkTYQlmfLxp7nC1vlgngOjOXcREREROSQnJwUCPX3xCNBPgj19zQugF6+/H6ZtjEB9Ndfc36zCdj7fOEHF8Qri9kWxCMAzEQTERERERkmCICTxPxTRgbgbduZUGv28HzhonJnb3cXqNycEZOShZ0XklG3mspmS7uLFsQ7n6CGys25REl30YJ4TUN8TbMgHpXCTDQRERERUVnu3LmfbTY2gH4w28wA2qSMmS9sq8y+IB5ViEE0EREREVGR0aPvB84BAeL7OTmxTNtC7s8XLrvI1sNViXytzubnCxctiNekhi/ScwoQfycb6TkFaBrii6Edwmx+3rctYTk3ERERETkunQ7w8AAKCozvGxsL1Ksn/5jIKA/OF/Z2dyl1vz3NF5Z1QTySzPbfSURERERkF8y2PdGtW0BoqLS+zDJbHUebL1y0IJ4tsNctxxhEExEREZHFmXx7ot27gR49pPVl4GzViuYLJ6hzEZNSODfaw1WJXI0Oieo8zhe2EHvecoxBNBEREZGDs3S2qGh7orRsDYJ93eHp6oEcjRbnE9RIUOdKm++p1wNKpbQB/fYb8Mwz0vqSRRTNFy4K2pIz8uDmrETTEF/0bGz7QZutMcln2oowiCYiIiJyYJbOFsm6PVFmJuDjI20gWq30oJusAucLWwdH2HKMq3MTEREROaiibNH5BDX8PF1Qt5oKfp4uOJ+gxtrD8YhNyTT5GCq9PdG3395fTdvYAPrB1bQZQNuFovnCjwT5INTf02aDNFvmEFuOWXoARERERGR+D2eLvN1doHRSwNvdBfUDVUjL1mDnhWTo9aadDyxpe6InnrgfOL/5pviTtWnDbaiITMwRthxjOTcRERGRAzImW2TKlYDFbE/kU5CHR4J9pZ3gzh2gatVKjpKIxHKELcdsd+REREREJNn9bFHZ2/54uCqRnJFn8mxRedsTVYu7jNdGDpB2UGaZiSzGEbYcYxBNRERE5ICsJVtUvD1Reg66TxqOx/49KO1ADJyJrIIjbDnGIJqIiIjIAVlFtuj/t6EKBzDP2L5HjwJt25pgUERUWfa+5RiDaCIiIiIHZLFs0ZUrwCOPSOur1xcuJkZEVs+etxxjEE1ERETkoMySLRIEYOhQ4LvvpPcnSfR6wS4DGLIdRVuO2RsG0UREREQOzCTZIo0GcHOT1nfxYuD996WfmwAU7gFedHEkT6uDu7MS9QJUiGhi+6W0RJbGIJqIiIjIwcmSLYqPB+rUkdY3L0960E2lxKZkYu3heKRlaxDs6w5PVw/kaLQ4n6BGgjoXQzuEMZAmqgQnSw+AiIiIiGzU118XzlFWKIwPoAXh/n8MoGWj1wuIPp+MtGwN6geq4O3uAqWTAt7uLqgfqEJatgY7LyRDr2eZPJFUDKKJiIiISJyCgvtBs0IBDB8uvm+/fiUDZzKJ2+m5iEstXChO8dAibAqFAsG+7ohNycLt9FwLjZDI9rGcm4iIiIjKd/s2ULOmtL537gBVq8o7HqpQtkaLPK0Onq5lb03m4apEckYesjVaM4+MyH4wE01EREREJU2dej/bbGwA/WC2mQG02Xm5OsPdWYmccoLkXI0Obs5KeLkyl0YkFT89RERERAQ0awacPSutL8uzrUaInwfqBahwPkENlZtziZJuQRCQqM5D0xBfhPiVnakmIsOYiSYiIiJyRElJJec3GxNAnzzJ+c1WyslJgYgm1eHv5YqYlCxk5hVAq9cjM68AMSlZ8PdyRc/G1blfNFElMIgmIiIichRRUfeD5uBg4/rq9feD5pYtTTM+kkV4oDeGdghDkxq+SM8pQPydbKTnFKBpiC+3tyKSAcu5iYiIiOyVTgc4V+LnHrPMNis80Bt1O6twOz0X2RotvFydEeLnwQw0kQyYiSYiIiKyJxrN/WyzsQH0woWVKtPW6wXcTMvB5aQM3EzLMftexJY+v7VxclIg1N8TjwT5INTfkwE0kUyYiSYiIiKydX/8AfTvL61vfj7g6lrpIcSmZCL6fDLiUrOQp9XB3VmJegEqRDSpbpbyYUufn4gcB4NoIiIiIluj1wMREcDu3dL6y1ymHZuSibWH45GWrUGwrzs8XT2Qo9HifIIaCepck8/DtfT5icixsJybiIiIyBao1ffLtJVKowLorG49cfNuNvQ6vewBtF4vIPp8MtKyNagfqIK3uwuUTgp4u7ugfqAKadka7LyQbLLSakufn4gcDzPRRERERNbqzBmgeXNJXf+7egN/3sy/X96866pJyptvp+ciLjULwb7uJfYkBgCFQoFgX3fEpmThdnouQv09ZTuvtZyfiBwPM9FERERE1kIQgA8+uJ9xNjaA/v8FwWKTM/DN+XScT1DDz9MFdaup4OfpgvMJaqw9HI/YlEzZhpyt0SJPq4Ona9m5GQ9XJfK1OmRrtLKd09D5BUFARm4B7mTlo0CnR16B1mTnJyLHw0w0ERERkSVlZwMqlfT+D5VnP1zeXJSd9XZ3gcrNGTEpWdh5IRl1q6lkWa3Zy9UZ7s5K5Gi08HZ3KXV/rkYHN2clvMoJsuU+f1q2BrEpWbiXo4FWp4cAwM1ZidTMfDwSZJIhEJGDYSaaiIiIyNxOn76fbTY2gL54scJtqIwpb5ZDiJ8H6gWokKjOg/DQeARBQKI6D+GBKoT4echyvorOfzcrH6dvpiM1Mw/uLkr4ebpAp9NDq9Pjz3NJsmbgqWLcbozsGTPRRERERObw2mvAjz9K62vEYmD3y5vLDlo9XJVIzsiTrbzZyUmBiCbVkaDORUxKYfDu4apErkaHRHUe/L1c0bNxdZPtUVx0/tvpOTgWn4b8Aj0CvF2h1QtIz9HC28MFzWr64u7/LzAmVwaeysftxsjeMYgmIiIiMgVBAJwqUfQncRVtS5RXhwd6Y2iHsOLAKTkjD27OSjQN8UXPxqYPnMIDvdG7aTBO30yHTqmAOrcASicnBPq4o16AF/y93ODqrLT4AmN6vYDb6bnI1mjh5eqMED8Puwvoud0YOQIG0URERERyOX4caNNGWt+ffwZeeKHSQygqbz6foIbKzblESXdReXXTEF/Zy6vDA71Rt7PKYkFiNW831K7qhQCVG3SCAFelE7zd7z9+uTPwxnKE7Ky55+MTWQqDaCIiIiKpBAFYsACYOlVaf72+cF60jCxZXu3kpLBYltfL1RkeLko4KxWo4u5a6n5TL3BWEUfJznK7MXIUDKKJiIiIjKHRAG5u0vtLLNM2hqXLqy3BUhl4QxwpO2vu+fhElsIgmoiIiMiQygTOn3wCTJgg73hEsHR5tblZeoGz8jhSdtbS250RmQu3uCIiIiIqy/z597ehMjaAzs+/vwWVBQLoIkXl1Y8E+SDU39NuA+giRRn4JjV8kZ5TgPg72UjPKUDTEF+LlUzfz86WHTh6uCqRr9WZLTtryq2nLL3dGVmnXbt24cKFC5Yehqx4GYiIiIgIAAoKgKAgIC1NWn8zlGmTYdaWgbem7KypFzez1moAMr+oqCh8+OGHyMzMRI8ePbBs2TJLD0lWDKKJiIjIcV2/DoSFSes7bBjwzTeyDocqJnaLKEsucPYwa5mrba7FzRxxPj4Vvpd/++03TJkyBdnZ2ejbty+OHj0KHx8fSw/NJBhEExERkWM5cADo1Ela3/R0wNdX1uGQOLa6RZQ1ZGfNvbiZtVUDkGkIgoBp06Zh/vz5AIB3330XJ0+ehJeXl4VHZnoMoomIiMi+6XRAjRpASoq0/izTtjhb3yLK0tlZSyxuZk3VACQfrVaLJ554AidPngQA+Pr6Qq1W223GuTwMoomIiMj+JCYWBs5StGkD/POPvOMhyexliyhLZme59RRVRnZ2NmrXro27d+8CKLzwkpmZCZVKZeGRWQ5X5yYiIiL78NNP91fTNjaAvnv3/mraDKCtijFZVGtR3grYllot/cHFzcrCrafoYQkJCVAoFFAoFFCpVHB2dkZubi4EQYBer3foABpgJpqIiIhslSAAXbsC+/ZJ709Wz9ayqNY4d9taFjcj63by5Em0atWqxG25ublwd3cv1VbsIn/2ikE0ERER2Y7MTKAyc+8YONsca9oiyhBrnbttDYubkfURBAG//PILXnrppRK3lxc4F7HGC0XmxnJuIiIism5bttwv0zY2gN69+36ZNgNom1SURU1U50F46DUsyqKGB6osnkV9eO62t7sLlE4KeLu7oH6gCmnZGuy8kFxc2m1uRYubNanhi/ScAsTfyUZ6TgGahvha/cJsJB+NRoMZM2ZAoVDAycmpOIDWaDQQBAGCIBgMoNcejsf5BDX8PF1Qt5oKfp4uOJ+gxtrD8YhNyTTXQ7Eoy1+yIyIiInqQXg+8/jqwfr30/gpm1OyFrWRRLbECtrG49ZRjUqvVeO6557B3794StxcUFMDZWXw4aC+L/MmBQTQRERFZXkEB4Ooqvb+VZJkdfZ6gqVh6iygxbGXuNreecgw3btxA7dq1S91ubOD8IFu4UGQuDKKJiIjIMhISgJAQaX2jo4GePeUdTyVxnqBpWXsW1ZbmbpP9EQQBJ06cQJs2bUrdp9Pp4ORU+Vm8tnKhyBz4KSYiIiLzEATgqaeAw4el9ddqAaVS3jHJxFoXlLI31pxF5QrYZG5arRa//vorBg0aVOo+vV5fKltcWbxQdB8XFiMiIiLTycy8vyiYk5PxAfSDi4JZaQBt7QtKkXkUzd3293JFTEoWMvMKoNXrkZlXgJiULKuZu022LTs7GxMnToRCoYCLi0uJAFqv1xcvDiZ3AA3YziJ/5sAgmoiIiOT177/SV9P+9FObW03bmHmCZN+4AjaZQnJyMlq0aAGFQgGVSoVFixYV32fqwPlBvFB0n/3n2omIiMj09uwBuneX1jcvD3Bzk3c8ZsR5gvQga5+7Tbbh4sWLaNy4cZn3PZwFNiexi/wV6Arw2T+fYcKuCQCAhlUbYvPAzWgU0MhiY5cTg2giIiIyXn4+UMFeogbZSJZZDM4TpIdZ89xtsk56vR5RUVEYMGBAmfdbMnB+WHkXipKzk/DK5hHYcG5DqT5X7l7Bb5d+s5sgmuXcREREJM7p0/fLtI0NoEePtrkybbE4T5CIyqLXC7iZloPLSRm4mZZTal2EvLw8TJ8+HQqFAkqlskQAHR4eXlymbU0BdJGiC0V3NGfRa2NrKOc4ocaSGmUG0EWGNB9ivgGaGC+JEhERUdkEARg/Hli2TFr/zExApZJ1SNaoaJ5ggjoXMSmFc6M9XJXI1eiQqM5zqHmCRFSovC3v2tRwxujXX8Lx48dL9Xn22WexefNmC4xWPK1ei1XHV2HsjrGi2nes3RGf9/4cTQKbmHhk5sUgmoiIiO7T6QDnSvw8sMKMiTkYmidYt5oKN9NyOEeWTEavFzgP20o8vOVdVnIiPhneu9z21phpflBqdiom7Z6Eb09/K6r9uLbjMLPzTPi6+5p4ZJbDIJqIiMjR3b4N1KwprW/btsDRo/KOx0aVN0/wvztZWLUvrlRGKqJJda7WTLIoL+vJ95j56fUCdpxLwskDOxG9bEKZbWrUaYCbsZet+iLHP7f+wYhtI3A66bTBtkqFCzoGTEWzKv0QHuiDiCbV4etu3+87BtFERESOaOFCYPJkaX2TkoDq1eUdj514eEGphzNSnq4eyNFocT5BjQR1Lrc9okrje8w6aDQazJw5EwsWLCjz/seejMCQGZ8hM68A6TkFuJ2ea1WLz+kFPb459Q0ioyJFtW9evTVa+kyAq77e/7/vnB3qfccgmoiIyBFoNIWBb3q6tP5WXm5ojfR6AdHnk5GWrUH9QFXxHq7e7i5QuTkjJiULOy8ko241lVVnpMh68T1mWWlpaejevTv+/fffMu9/ovdAvDRudonbrGnLu7TcNEzdMxVfnvxSVPsRj4/AvG7z4OdWBav2xeF8gtph33cMoomIiOyVWg34+Unr278/8Pvvsg7H0dxOz0VcauFCY0U/MosoFAoE+7ojNiXL6jJSZDv4HjO/8+fPo2nTpuXeP33OAmTV7wU/Txer3PLu38R/MWr7KBy9JW4azpq+a/BmyzfhpLi/qdPNtByHf98xiCYiIrInR48C7dpJ63vjBhAaKu94HFi2Ros8rQ6ermVvbWVNGSmyTXyPmZ4gCNi0aRMGDRpUbpuNGzdi4MCBAAqrA4qytCo35xJBZtGWd01DfM225Z0gCPj+zPeIjIqERqcx2L55UHN82edLtK3Zttw2fN8xiCYiIrJtWi3gUjrbIZpeX7jvM8nOy9UZ7s5K5Gi0VpmRItvH95hpaDQaTJw4Ecsq2N5v165d6N69e6nbrWHLO3WeGjP3zcSyf8of/4OGNR+GBd0XINArUFR7vu8YRBMREdmemzeBWrWk9+f8ZrMI8fNAvQCV1WSkyP7wPSaflJQUdOnSBRcvXiy3zbFjx9C6dWuDxzK05Z0pFtw6n3Ieo7ePxoHrB0S1X/H0CoxoNQLOTsaHg3zfMYgmIiKyDfv2AV26SOt7+jTQrJmcoyERrCEjRfaN77HKOXHihMGg+MKFC2jUqJHRxy5vyzu5XgtBELDpwiYM/2M4MjWZBts3CmiEL/t8iadqP1Xpc/N9BygEK9vdOyMjA76+vlCr1fDx8bH0cIiIiCxDEIC5c4EZM6T1Z5m21XhwD998bWGZY3igymQZKXI8lnqP6fWCyYJEuTw4Rk8XJaI3/4TIyOEV9rl27RrCwsLMM0AjZGmyMGf/HCw6skhU+1eavoJPenyCYO9gk4zH3r7bjIlDGUQTERFZi8REoEYN6f2t6086PcAWgg2ybeZ+jz0YQOVpdXB3VqJegAoRTawngIpNycQfJ+LxzSfTcWFfxbsNxMfHo3bt2mYamXhX717FmO1jsOu/XaLaL+6xGGPbjoWLshJrZRjBnr7bjIlDWc5NRERkSb/8Arz4orS+P/4IvPKKvOMhk3ByUtjtVi+2zJ4CAHO+x2JTMrH2cDzSsjUI9nWHp6sHcjRanE9QI0Gdi6EdwiwaSN+4cQMdnuyIWzevV9guNTUV1apVM9OoxBEEAVsub0FkVCTu5Nwx2L5elXpY3Xc1utXtZobRleao320MoomIiMxJrwciIoDdu6X112oBpVLeMRE5IFvIpFojvV5A9PlkpGVrUD9QVbyolLe7C1RuzohJycLOC8moW01ltgsSgiBg37596Nq1q8G2C7eeRrxai6YhvvD3r2qG0RmWW5CLBYcWYM6BOaLav9DoBSzpuQShvtyS0FIYRBMREZmaIABOTpXrT0SysfZMqjW7nZ6LuNTCxaQUD627oFAoEOzrjtiULNxOzzVphlKj0eCLL77Ae++9Z7DtnF/+gZePX/G/g1FgljFW5L97/+HdHe8i6mqUqPbzu87H+Hbj4ebsZuKRyS8uLg5ubm6oWbOmpYciG6P+oi9YsACtW7eGt7c3AgMD8cwzz+DKlSsl2giCgJkzZ6JGjRrw8PBA586dceHCBVkHTUREZPWOHi1c2EuhMD6A/uabwsC56D8iks3DmVRvdxconRTwdndB/UAV0rI12HkhGXo9P3tlydZokafVwbOcPYA9XJXI1+qQrdHKfu67d+9i4MCBUCgUcHNzqzCAHv7tIXyy4zKW7LxSIoA29Rgrsu3qNoQsCYFilgL1PqtXYQBd06cmtg3eBuEjAcJHAiY/NdlmAujc3FwsXLgQ9evXR926dTFixAhLD0l2Rv1V379/P0aPHo2jR49i165d0Gq16NmzJ7Kzs4vbLFq0CEuWLMHKlStx/PhxBAUFoUePHsjMNLz0OhERkc0SBKBPn/uBc7t2xvXXaO4HzcOGmWaMRGRUJpVK83J1hruzEjnlBKC5msJVmr3KCbKNdeHCBQQHB0OhUKBatWrYtGlTuW3z8/MhCAJu3M2GytPLbGMsdzzafMw7MA+KWQooZinQ96e+SMhMKLd9vwb98N/Y/yB8JODmezfRu35vk45PLoIgYPv27WjXrh3q1auH1q1bo2rVqrh06RL+++8/7Nq1y66y0ICR5dw7duwo8e+1a9ciMDAQJ0+eRMeOHSEIApYtW4apU6fiueeeAwB89913qF69OjZs2IC3335bvpETERFZmloN+PlJ788sM5HZ3c+kepR5v4erEskZeWbPUtqKED8P1AtQ4XyCGio35xIXIgRBQKI6D01DfBHiV/bzWxG9XsD1O5nYvn0bxgwdLKqPVquF8qF1Ikw5RkNuqG/gvej3sPnSZlHtZ3ScgUlPToKHi/xjMaUDBw6gU6dOxf/u3bs3fvvtNwQFBVlwVOZTqcsvarUaAODv7w+gcE+1pKQk9OzZs7iNm5sbOnXqhCNHjpQZROfn5yM/P7/43xkZGZUZEhERkWklJAAhIdL6TpsGzBG3cAwRmcaDmVRv99LbAJkrS2mrnJwUiGhSHQnqXMSkFGb0PVyVyNXokKjOg7+XK3o2rm7UomIZGRmYMX8Rln88T1R7vV5fqorA1GOsyJ7/9iAyKhL/3fvPYNtAr0Cs6bsG/Rv2r/AxWJvs7Gy0bNkSV69eLb5t4cKFmDhxogVHZTmSvx0EQcD48ePx5JNPokmTJgCApKQkAED16tVLtK1evTquXy97ifkFCxZg1qxZUodBRERkWoIALFwITJkirX9WFuDlJe+YiEgyS2Qp7WkrLQAID/TG0A5hxaubJ2fkwc1ZiaYhvujZWNzq5vHx8XjnnXcQFSVuYS1DgbMpxlieAl0Blh1dhg93fyiqfc96PbHi6RVoULWB5HOamyAIGD16NFatWlV8W5UqVXD37t3iBKojkxxEjxkzBmfPnsWhQ4dK3ffwG1wQhHLf9JMnT8b48eOL/52RkYHQUC7XTkREFpSZCfj4SO/PMm0iq2XuLKW9bqUVHuiNup1Voi8O6PV6HD16FH379sW9e/cMHl/p4oJFUecQk5KFpiG+EITC5SZMOcaKJGYmYsKuCdhwboOo9pM6TMLUjlOhclUZfS5L2bFjB55++ukSt61ZswZvvfWWTWXNzUFSEP3OO+9g69atOHDgQIlJ4kU18ElJSQgODi6+PSUlpVR2uoibmxvc3GxjpTkiIrJjx44BbdtK6/vyy8AGcT+sSDx7y96R9ahbTYVeTYKw51IybqfnQqlQwN1Fnizlg+x9Ky0nJ0WFW0RlZ2dj8+bNeP3118UdT+mMxX+W3NWnsltmGRpjRQ5cP4C3o97G5TuXDbb1cfPBmr5r8FLjl2wm4Lxz5w4CAgJK3c5ss2FGBdGCIOCdd97Bb7/9hn379qFOnTol7q9Tpw6CgoKwa9cutGjRAkDhHm779+/Hxx9/LN+oiYiIKksQgDVrAKlbb7BM26TsNXtHlvfgeyu3QAsIQKCPO7o3CkT7etVku1Dz8FZaRYGVt7sLVG7OiEnJws4LyahbTWVXF4cSEhKwcuVKLFiwQFT7eg0eQc8ZP6JuNRWUZTwP5lzoTavX4ovjX+DdHe+Kat85rDNWPr0SjQMbm3hk8hAEAU8++SSOHDlS4vavvvoKQ4cOLbVAG5XPqCB69OjR2LBhA37//Xd4e3sXz4H29fWFh4cHFAoFxo0bh/nz56N+/fqoX78+5s+fD09PTwweLG6FPSIiIpPRaIDWrYGzZ6X1Z5m2Wdh79o4s5+H3Vo3/f28lqvPw5/kkBPm6y/beMmYrLamZUmsgCAJOnz6NyZMnIzo6WlSf/v374/fffwcA3EzLwdJdVy220FtKdgom7p6IdafXiWr/3hPvYWbnmfBxq8SUHzPauHEjXn755VK337x50+62nTIno96NRRPLO3fuXOL2tWvXYsiQIQCADz/8ELm5uRg1ahTu3buHtm3bYufOnfD25h87IiKygFOngMcfl9a3QwegjLU/yHQcNXtHpmfu95Y9b6WVl5eHPXv24OWXX0ZmZqaoPmPHjsXy5ctL3W6Jhd6O3jqKt6PextlkwxdU3Z3dsabvGrz62Ks2UaZ969atMteXWr58Od5++21Oo5WJ0eXchigUCsycORMzZ86UOiYiIqLKWbBA+mrat25J38KKKs1RsndkHg/Oq8/ILUBsSqbZ3lv2tpVWamoqfv75Z4wePVp0n/Hjx+PTTz+tsI05FnrT6XX4+tTXGLFN3PSddjXb4Ys+X6B5UHPJ5zQXQRDg5ORU5n3nz59H48a2UWpua2zjU0tERFQRrRZwKf0jVTSWaVsNe87ekXk9PK8+v0CPm2k5aBVWpcygVu73liUyrHISBAEXL17EN998g6VLl4rut2TJErz33ntGncsU21HdzbmLKXumYM2pNaLaj2o1CnO7zkUVjypGn8vc5s2bh2nTppW6fcKECZg+fTp8KrO7BInCIJqIiGxTVhYgdapQixaFZd5kdewte0eWUda8+uSMXFxK1OLUjXtoHeYPf6+SZa1yv7fMvZWWHAoKCnDw4EEsWLAAu3fvFt3v888/x6hRoyp1bjm2ozqVeAojt43EsdvHDLZVQIGv+n2FoS2GwklRdibXWpS3ijYAHDhwAB06dCg3G02mwb9ARERkO2bNAqROF4qJAcLDZR1OWbgtU+XYevbO0vj+K3/uc7CvB2pX9cR/d7IRm5KF1mGuxfeZ6r1ligyr3O7du4cdO3bgrbfeQk5Ojuh+W7ZswYABA2Qdi7HbUekFPb47/R0ioyKh1RuuIGgZ3BKr+qxCm5A2lRmmyQmCgMDAQNy5c6fUfd27d8f69esRGBhogZFREQbRRERkvTQaoDKLoJi5TJvbMlWeLWbvrAXff4XKm1evUCgQHuiNtGwNrt/NQc0qngj0cTP5e0uODKvcYmNj8fvvv2PChAlG9Tty5AjatWtnolGJo85TY8ZfM/DZsc9EtX+rxVuY320+ArzKzuRai127dqFnz55l3vfDDz9g4MCBcKnMtCWSFYNoIiKyLrdvA1K33WjQALhyRd7xiMRtmeRjC9k7a8P3330Vzav393JFy9pVcOr6PaRl5yNHozXLe8vYDKvcdDod/v77b2zatAkrVqwwqu+lS5fwyCOPmGhk4pxLPodR20fh0A1xuyWsfHolRrQaAaWT9e57nJSUhODg4DLvUygUiImJQb169cw8KhKLQTQREVne3btAtWrS+l6/DtSqJe94jMRtmeRnjdk7a8X3X0mG5tV7uCjRKNgHL7etBR8PF7t9b2VmZmLnzp344osvsHfvXqP63r59GzVq1DDRyAwTBAEbz29EZFQksjRZBts3CWyCL/t8iQ61OphhdNJVtEXWxIkTMX36dHh5eZlxRCQVg2giIjI/vb5wD+ajR6X1t7LVtLktk2lIyd454pxgS7//rO05FzuvvlVtf7t7b1y/fh07d+7EqFGjoNUat8p4amoqqkm9mCmDzPxMzN4/G4v/Xiyq/auPvYpF3Rch2LvsbK41WLduHYYOHVru/QcPHkSHDh1sYv9pKolBNBERmcf160BYmPT+VhY4P4jbMlkHR50TbMn3nzU+5440r16v1+PEiRPYu3cvJk+ebHT/rKwsi2Y+L9+5jHf+fAe7/xO3EviSnkswps0YuCitc25wdnY2VCpVufe3b98ev//+u0UvVpA8GEQTEZHpbNwIvPyytL5xcUDduvKOx0S4LZPlOfKcYEu9/6z5ObfnefU5OTnYs2cPdu7ciZUrV0rq7+Eh3wrkxlQiCIKAzZc2IzIqEmm5aQaPHe4fjjV916BLnS6yjVduHTp0wJEjR8q9/+uvv8Ybb7wBZ2d+/9sTvppERCQfQQCGDgW++05af70esMGyNm7LZFmOPifYEu8/W3jO7WlefWJiIqKjo7F27VocOHDA6P4FBQUmCeLEVCLkFORg/sH5mHdwnqhjvtT4JXza81PU9JG4wKSJHTt2DG3btq2wzeXLl9GwYUMzjYgsgUE0ERFVTkYG4Osrvb8Vl2mL5Ujlo9bI0nOCLc0S7z9bec4tvSq2VIIg4OzZszhw4ADGjh0r6RhXk9SoX91H5pHdV1ElwoWUq7iYuxz7b+wUdawF3RZgfLvxcFW6mmy8UuXn58Pd3b3CNm+//TaWLl0qa4afrBuDaCIiMl5lyrQPHgSefFLe8VgBey4ftXack27+9x+fc/nl5+dj3759OH78OKZPny7pGJ9GXwYAxKRkYdfFFNQL8DbJxbuyKhEupu3DprhpyChINdi/lm8trO67Gr3Ce8k+NjlMmDABn376aYVttm/fjl69enFRMAfFIJqIiAzT64GOHYHDh6X3d4AfGvZUPmpLOCe9kDnff3zO5ZGamoro6GgcOXIEq1atknSMJTuvlLrN1JUAt9NzcSX5Lq7k/Igv/xY3L3tAwwFY1msZwvzCZB9PZYkp0W7QoAH279+PoKAgM42KrBm/2YiIqGzZ2UAFq4xWKCIC2LFD3vHYCFstH7VlnJN+n7nef3zOpREEAZcvX8a+ffvwww8/4O+//5Z0nEuJany2JwZ1q5X9HW2qSoAb6hsYt2Mcfrv8m6j2Yx6fjEUR0+HhYl3vA71eD6VSabDd/Pnz8eGHH4pqS46FQTQREd0XEwM0aCCt76lTQIsW8o6HSATOSTc/PufiFRQU4NChQzh9+jTGjx8v6RgeHh7Iyckp/vfNtByzVQLsituFyKhIxKfHG2zr7VINL9abjdqeHZGeU4D32jewmgD622+/xZtvvmmw3T///IM2bdqYYURkyxhEExE5MkEAmjQBLl6U1t9ByrTthTFb0dgazkk3Pz7n5UtPT0d0dDSuXr2KGTNmSDpG586d8ddff5V5nykrATQ6DZb+vRST9kwS1f4Rv6fwbJ1pCPAIKz5/TEqWxSsRLl26hEaNGhls17dvX/z444/wrcwCmeRwGEQTETmae/cAf3/p/e1gNW1HJGYrGlvHOenmx+f8vri4OOzZswfHjx/H119/LekYEyZMwCeffGKwndyVALczbmPCrgnYeH6jqPZTnpyCgY+8g/8dS0VatgbuCndo9XqLViLodDrR23itXbsWb7zxBhcFI8kUgmBdv4YyMjLg6+sLtVoNHx/TLctPRORQ4uOBOnWk9T17FmjaVNbhkHmV3orGGTkabfGP3aEdwuwmkCbbZkvVEjqdDkePHsXJkyfx9ddf49y5c5KOs2nTJrz44ouS+j54cSxfW1jCHR6oElUJsD9+PyKjInH17lWD5/Fz98OavmvwQqMXSgSelTm/HBYuXIjJkycbbOfj44Njx45x72aqkDFxKDPRRET26tdfgRdekNaXZdp2o6ytaADA290FKjdnxKRkYeeFZNStprLaYIUcgy1US2RlZWHnzp2Ij4/H+++/L/k4hw8fRvv27Ss9HmMqAbR6LT4/9jnGRY8TdeyudbpixdMr0Cig/JJoc1ciJCcni14de/To0Vi0aBE8PbnQI8mPQTQRkb3IyAAqM6fLugqTSCa303MRl1pY7vlw6aJCoTD5VjhkOyyZBS5dLeGBHI0W5xPUSFDnWrRa4ubNm9i5cydu3LiB2bNnSz7O6dOn0axZMxlHVqiiFdmTs5Lx4e4P8f2Z70Uda/wT4/FR54/g4ya+GtSUK8ILgoAaNWogKSlJVPutW7eib9++LNMmk2MQTURkyw4eLNy/WYroaKBnT3nHQ1YnW6NFnlYHT9eyF/gx1VY4ZFssmQW2tmoJvV6PU6dO4e+//8Y///yD9evXSz7WjRs3EBoaKuPoDPv75t94O+ptnEsxXF7u6eKJNX3XYHDTwVYTeH7//fd44403RLVt0aIFtmzZglq1apl4VEQlMYgmIrIlggB89BEwZ460/izTdjhers5m2wqHbJOls8DWUC2Rm5uLPXv2IC4uDp988glu374t+Vjp6elmXelZp9dhzck1GLV9lKj27UPb44veX6BZkPxZcSnu3bsHfyMWu5w7dy7Gjx8PDw/r2DqLHBP/YhIRWTu9HggIANLSpPVnmbZDM+VWOGT7rCELbKlqiaSkJERHRyM1NRUffPBBpY6l0Wjg4lL6IpWp3M25i8l7JuOrU1+Jaj+m9RjM7jIbVTyqmHhk4nTo0AFHjhwR3X7fvn3o2LGj1WTLiRhEExFZo//+A+rVk9Z3926gWzd5x0M2S+6tcMi+WEMW2FzVEoIg4Ny5czh48CBu3bqFhQsXVup4er3erEHdyYSTGLFtBE4knDDYVqlQYk2/NRjSfAicFE5mGF3Fjhw5gg4dOohu/8wzz2DlypUICQkx4aiIpGMQTURkDQQBeOst4NtvpfVnmXal2NK2OlKEB3pjaIew4jmvyRl5cHNWommIr9m2onmQvT/ftsQa5sybsloiPz8f+/fvx4ULFxC1Yyf27txRqbGac2dYvaDHutPrMPyP4dALeoPtW9VohVV9VqFVjVZmGF3FcnNzjV4Ve/Xq1Xj11Ve5mjbZBAbRRESWkp8PuLtL6+vvD9y9K+94HJQtbKsjB3NvRVMeR3m+bYU1zJmXu1rizp07xWXaEyZMgE6nq9T4zBk4p+elY/re6Vh5fKWo9sNbDsf8bvNRzbOaiUdm2JAhQ/Ddd9+Jbh8SEoLNmzejdevWLNMmm8MgmojInO7cKZzfLMXRo0DbtvKOx8FZekElczPlVjRiONrzbQusZc58ZaolBEHAlStX8NdffyEjIwOTJk2q1Fi6d++OXbt2VeoYxrh85zLe3PomjtwUN0f4i95fIPLxSCidlCYeWcVOnz6NFi1aGNXnnXfewcSJE1mmTTaPQTQRkalFRQH9+knryzJtk7GGBZUcCZ9v62RNc+aNqZbQarU4fPgwTp8+jZiYGHz++eeVOve4ceOwdOnSSh1DLEEQsP/6fhy+cRh/XP0D/9z+p8L2j1V/DKv6rEL70PZmGV959Ho9lErjA/cNGzZgwIABLNMmu8IgmohIbpUp0wa4mraZWMOCSo6Ez7f1sqY58xVVS6jVakRHRyMhIQE//PADTp06ValzdX31HTTrOwzv9Whg8vdcZn4mZu6biSVHl4hq/3qz17Go+yJUV1U36bgMWbp0KcaPH29Un44dO2LJkiVo0aIFnJwsv6gZkSkwiCYikkNMDNCggbS+x44BrVvLOx4yyBoWVHIkfL6tm7XMmX/Yf//9h927dyMnJwfvvfdepY83ZMZKPPZkDwCAVq9H/J1sk73nLqVewpg/x2Dvtb0Vtmsa2BQCBLzV4i2MbjMazk6W+3melpaGqlWrGt1v9uzZGDZsGMu0yWEwiCYikuqXX4AXX5TWl2XaFmcNCyo5Ej7f1s/Sc+YBQKfT4dixYzh+/DjS0tIwa9asSh9zzOe/o279R0rdLvd7ThAE/HLxF0RGRSI9L91g+1GtRuGDDh8gzC9MlvNLIQgC3NzcUFBQYFQ/T09PrF+/Hj179mSZNjkk/qUiIhJLrwdeeQXYuFFaf5ZpWxVrWVDJUfD5pvJkZWVh165duHHjBg4cOIDNmzdX+pgpKSmoWrUaVu2Lw/kENQRBMMl7LluTjfkH52P+ofmi2g9qMgiLeyxGiI/lMrbr1q3D0KFDje73yiuvYNy4cWjZsqUsZdrc6o5sGYNoIqKK/PcfUK+etL5//w088YS84yHZWNOCSo6Azzc96NatW9i5cycyMjIwdepU5OTkVPqYubm5cH9oPQpTvOdi02Lxzp/vYEesuD2nP+7+McY9MQ6uSlejziMXKXs2F/nss8/w3HPPyV6mza3uyNYpBHNufidCRkYGfH19oVar4ePjY+nhEJEjWr0aGDFCWl+WaducB3/M5WsLyzvDA1VmX1DJUfD5dkyCIODUqVM4cuQIcnNzMXHiRFmOq9PpDGZF5XjP/XHlD0RGRSIpK8lg2zC/MKzuuxo96/UUdWxTCAwMRGpqqtH9mjdvjlmzZqF79+4mK9MuvdWdM3I02uILG9zqjizFmDiUQTQRkVYL1KoFJCYa3zciAtghLhtB1otlhebF59sx5ObmYu/evYiJicGVK1fw5ZdfynJcvV5faoV3w32Me8/lafPw8aGPMXP/TFHHf+aRZ7AsYhlq+9U2alxyuXjxIho3biyp7/vvv49BgwbJVqZdEb1eKC6xf3CrO6DwQktMShaahvhiRKd6/E4gszMmDmU5NxE5ptxcQOpV9iNHgHbt5B0PWZQ1LKjkSPh826/k5GRER0fj3r17+Oqrr3DhwgVZjltezkdscCzmPRefHo/3ot/DlstbRI1pdufZ+KDDB3B3rsSWhhIJglCpgHfNmjV4+umnUbNmTRlHZZg1bnXHi3okBYNoInIcX30FREZK68sybSKiUgRBwPnz53HgwAHk5ubigw8+kOW41apVM1iOLMe82ujYaERGReKG+obBtsGqYKzuuxr9GvYTdWy5zZgxA3PmzJHUd8CAARg2bBi6desGLy8vmUcmnrVtdce52SQVg2gisl86HeBcia8565rtQmQUZlfskzW8rhqNBvv378eFCxeQkJCATz75RJbjDh8+HGvWrBHVtvS8Wg/kaLQ4n6BGgjq33Hm1Gp0GS/9eikl7Jok6T+/6vbG813KE+4cb9VjkIHXP5iJz5sxBREQEHn/8cZOXaYtlTVvdSX0PEQEMoonI3ty7B/j7S+t79SpQv7684yGyAGZX7JMlX9e7d+8iOjoaqamp2Lp1K/bu3SvLcb/99lujt1vS6wVEn09GWramxLxab3cXqNycEZOShZ0XklG3mgpOTgrcyriF93e+j00XNok6/tSnpmLKU1Pg6WL+KQfGzvV+UO3atTFjxgz07NnT7GXaYlnLVnfGvoeIHsYgmohsX2oqEBgorS/LtMlI1pAJrAizK/bJEq/r1atXsXfvXmRnZ2PChAmyHffo0aNo27at5P5i5tX+dW0fFp99GtfSYw0ez9/DH2v6rsFzjz5XqSBWin///RctW7aU3H/kyJGIiIhA9+7dLVqmLZa1bHVnjXOzybYwiCYi26PTAW+9BaxbJ60/y7RJImvP8DK7UnnWeJHEXK+rVqvFkSNH8O+//yIpKQkLFy6U6yEgOTkZgVIvdj6krHm1Wp0Ge279gOjbi0Qdo1udbljx9Ao8GvCoLGMSq7ILggHAp59+iqeeesqqyrSNER7ojaEdwoq/S5Mz8uDmrETTEF+zbXVnbXOzyfYwiCYi23DnDhAQIK0vV9MmGdhChpfZlcqx1oskpnxd1Wo1du7ciYSEBOzbtw9btmyRbdz5+flwdXWV7XhFiubVpmQn4a+kpTiR+ruofhPaTcCMTjPg7Wbe13Ly5MmVuiDRtWtXDB48GD179kRoaKiMI7Oc8EBv1O2sstgFK2uam022ie8MIrJeu3cDPXpI68sybZKRrWR4mV2Rzpovksj9ul67dg27d+9GRkYG5s6di/T0dNnGKmUPZ2Mcun4Yb22NxJW0iwbbujh54OOuKzGu/VCzlmnfvXsX1apVq9Qxpk2bhlatWtlMmbYUltzqzlrmZpPtYhBNRNbl5ZeBjRul9WWZNpmIrWR4mV2RxtovklT2ddXr9Th27BiOHTuGxMREWcu0gfL3cJaDTq/Dlye+xJg/x4hq7+vUFM1U4/FUWEvczS6Am8YXgmD6a6pubm7QaDSS+7u7u2PhwoVo164dWrVqZZNl2rbEWuZmk+3iX1Eisqz8fMDdXVrfv/8GnnhC3vEQlcFWMry2kl2xtnnH1n6RRMrrmp2djV27duH69es4dOgQfvnlF9nG06xZM5w+fVq24z3sTs4dTN49GV//+7Wo9lWFAWjgMQw+bn7w93JFvQAv+Hu5wdVZabLXLS4uDuHhldv26rXXXkOnTp3sqkzblljD3GyyXQyiicj8du4EIiKk9WWZNlmArWR4bSG7Yo3zjq39IonY1zUxMQHR0dG4e/cuPv/8c1y/fl22MUybNg1z5syR7XgPO377OEZsG4FTiacMtnVSOOOlurNRx7M3jl27B41WhypebmhRyw8+7i7FFxnkfN3kWBAMAObPn49HH30U3bt3h0qlqvTxqHIsPTebbBeDaCIyPUEozBgfOya9P5EF2UqGF7Du7Iq1zju2hYskZb2urkon+OXcgvPNGHz9zx18/PHHsp5z48aNGDhwoKzHLKIX9Fj771pERkVCL+gNtg9yb4IBYdPR0L958W0ZuQVwVjrB1dkJ+Vo9FFCU+GxW9nX7/vvv8cYbb0jqW6Rx48aIjIzEE088wTJtK2XJudlkuxhEE5Fp5OQAUhdDuXoVqF9f3vEQVYItZHgfZI3ZFWued2wrF0nCA71R4wln/BK1A5firuDMiX/w5x9bZD3HmTNn8Nhjj8l6zCL3cu9h2t5p+OLEF6Lav/3425jXdR5SM1zw2Z4Y1PUrmbn1dndGFU9XpGTkQaEQoNHdD8alvG4ajQZubm7iH1A5xo8fj0aNGqFHjx6oVatWpY9HRNaHQTQRyefaNaBuXWl9mW22GtY2X9VaWHOGtyzWll2x5nnH1n6RJCUlBdHR0UhKSsLXX3+Nq1evynr87OxseHqa5jk/k3QGI7eNxN+3/hbV/ss+X+Ktlm9B6aQsvi0nL6fMSgGFQoHwQBXSsvORmaeDRquHVq836nXr168foqKipD/A/7d48WLUq1ePZdpEDoJBNBFJJwhA27bA8ePS+5NVscb5qtbEGjO8tsLa5x1b00USQRBw8eJF7N+/H9evX8eiRYtkP4dGo4FS6Yzb6bm4kaGFV16O6PdyRRfaBEHAj2d/RGRUJPK0eQaP1ax6M3zZ90s8UbP8RSIrqhSo4umCQG93BPoAWp0e8XeyK3zdEhISEBISYnBchvTu3RsRERFo27YtWrduzTJtIgfDIJqIjJOdDUi9yn7xIvDoo/KOh2RjrfNVrY21ZXhtha3MO7bURZKCggIcOHAA586dw8GDB7F582bZz/HgHs5SL5iV1a9GFQEXs7/B2rOfixrHkOZDsLDbQlRXVRfV3lClQK2qnnijfW14uDiX+brJtUf0zJkzUbNmTZZpExGDaCISIT4eqFNHWl9mm22CNc9XJftgK/OOzXmRJC0tDdHR0bhx4wbWrVuHy5cvy3p8Dw8P5OTklLpd6gWzB/spXW9jZ8o8xGWIWzByea/lGNV6FJydpP30NKZS4Pjx46jVpo2k8zzI3d0d8+fPR1hYGHr06MEybSIqxiCaiMr200/A4MHS+jJwtjnWPF+V7IO1zzs2l5iYGOzduxexsbFYvHix7McfO3Ysli9fXu79Ui+Y6XR6LPhrLX68OgUafbbBcTxS7RF82edLdArrVPkH9f/KqxRQKOTLNr/xxhto2bIly7SJqEIMoomoUG4uIHVhmcuXgYYN5R0PmZW1z1cl+2BN847NRavV4u+//8bJkyexf/9+bNmyRfZz7NmzB127dhXV1pgLZv4qAXMPzMXCwwtFHfsRn6fx/fMr0LpWPaMfg1hFlQK//vorXnjhBVmOuWDBAlSrVg09evRA7dq1ZTkmEdk3BtFEjuzsWaBZM2l9mW22K7YwX5XsgyMszpaRkYGdO3ciJiYG3333Ha5cuSL7ORISEhAcHGx0P0MXzLJ0N/DL9dlYuuKoqOP1rf0BOga/DsAZ8Xey4e0aYPSYxJBr+ykAaNCgAUaOHInatWuzTJuIJOGvISJHIgjAhx8CUkoIp08HZs+Wf0xkFWxlvirZB3tcnO369evYtWsXLl26hCVLlpjkHPn5+XB1da3UMR6+YCYIAi7c24NNcTOQVXDXYP8qrjUxMHwOGvi1L3F7Zl6B7Bfaxo8fj6VLl8pyrHfffRd169ZFmzZt0KZNG5ZpE1GlMIgmsnd6PaBUGm5Xlnv3AD8/WYdD1onzVYmMo9frcfz4cRw9ehR//fUXfv/9d5OdR675vkDhBbNQf2esv7QcJ+99JarPc48+h097LMG2fwtwPkGN+r4lM7dyXWi7d+8e/P39Jfd/2OLFi+Hr68sybSKSHYNoInuUmAjUqCGtL8u0HZYjzlclMkZOTg52796Ns2fP4vvvv0dMTIzs53B2dkZBQYHsx7127xrGRY/D1itbRbWf22Uu3m//Ptyd3Ytvi2iSKfuFNj8/P6jVaqP6lOepp57Cc889h1q1aqFHjx7w9uZ3FhGZhkIQrOsXc0ZGBnx9faFWq+Hj42Pp4RDZBkEAXnoJ+OUX4/sOHQp8+638YyKbpdcLdj1flcgYCQkJiI6OxpkzZypc9boy3nrrLXz1lbissDH+jPkTkVGRuJVxy2BbL+cAvN5wHsZ3HCR6n+h8beFaCeGBKtEX2q5cuYJHHnnEqMdRkSlTpqB69epo06YNWrduDaXUyisiG8C/z6ZlTBzKTDSRrSooAKTOjdNoAJfSi0cRAfY5X5VILEEQcObMGezfvx979uzBH3/8YZLz/PLLL3j++edlPWa+Nh9L/l6CKXuniGrfp35fTGy3AAEetUT/IJeyMJyc5egAsGTJEnh7e6N79+4ICwuT9dhE1urBC1h5Wh3cnZWoF6BCRBNWilkCg2giW5KRAfj6SutrXUUnZAN4xZscRX5+Pv766y8cO3YMP/zwA2JjY01ynlu3biEkJETWY95U38T4nePxy0VxlUjTnpqGyU9NhqeL9Atlhi60nT9/Hk2bNpV8/If16dMH3bt3Z5k2OazYlEysPRyPtGwNgn3d4enqgRyNFucT1EhQ52JohzAG0mbGIJrI2v31FyBy/88S5s8HJk+WfzzkEHjFm+xdamoqduzYgWPHjmHlypUmO49Go4GLzJU/e6/txdtRbyM2zXCwX82zGtb0XYNnHnlG9oxwEUEQZF/tetasWfDz80Pr1q3Rpk0blmmTw9LrBUSfT0Zatgb1A1XFn2Nvdxeo3JwRk5KFnReSUbeaihe6zYhBNJG1qUyZdk4O4MEtiKhybPGKN7PmZIggCLh06RJ2796N6OhobN++3STnCQgIQEpKiqzHLNAV4LN/PsOEXRNEte9RtwdWPL0CDas1lHUcD9q+fTv69Okj6zEnzVqAKr4+eKHf06hbt46sx3ZU/G60fbfTcxGXWriY38MXwhQKBYJ93RGbkoXb6bkVVojwvSAvBtFE1uDmTaBWLWl9WaZNMrLFK97MmlN5CgoKcPDgQezfvx/r169HXFycSc4zceJELFy4UNZjJmUlYcLOCVh/br2o9h+2/xDTO02HylVluLEEer1e9mzwCy+8gAaPPY4UvTfcajeH2sUd+c5K/BmvQ4Qqk5/fSuJ3o33I1miRp9XB07XsJImHqxLJGXnI1mjLPQbfC/JjEE1kKcuWAe+9Z3y/9euBwYNlHw4RIN8Vb3Oxxaw5mda9e/cQHR2Nffv2YfXq1SY7z/r16zFY5u/iQzcO4e2ot3Ex9aLBtt6u3ljTbw0GNh5osjLtTZs2YeDAgbIec+7cuVCpVGjdujWq1mmE74/ehHO2BoG+7vB0debnVyb8brQfXq7OcHdWIkejhbd76akhuZrCVfK9XMsO6/heMA0G0UTmIghA8+bA2bPG9y0oAJz5cSXTk+OKt7nYYtacTCM2NhY7duzAtm3bsGPHDpOd59KlS7Juz6TT6/DliS8x5s8xotp3rN0Rn/f+HE0Cm8g2hhLj0engLPPfGk9Pz+LAuXv37qhTp7BMW68XsGpfHD+/JsDvRvsS4ueBegEqnE9QQ+XmXOKimSAISFTnoWmIL0L8Sv/d5nvBdPirnMiUEhIAqSuxskybLKCyV7zNyday5iQfnU6Ho0ePYseOHdiwYQP+++8/k50rMzMTKpV8JdKp2amYtHsSvj39raj249qOw8zOM+HrLnFnBgNWrlyJd955R9Zjvvzyy2jbti1q1qyJHj16lLnfKj+/pnM7PRexKZlQuSlxN1sDV6UTvN0Lgy8+t7bHyUmBiCbVkaDORUxK4WfGw1WJXI0Oieo8+Hu5omfj6mUGwfycmY7lfwUR2ZtFi4CJE43vFx0N9Owp/3iIjFCZK97mZktZc6q8zMxM7Ny5E3/++Se++eYbk55Lr9fLWiJ9/PZxvB31Nv5N+tdgW1elK9b0XYPXmr0GJ4W8K14Dhdt5ubu7y37c2bNnw8fHB61bt0bbtm0Nzp/m59d0LiVl4EJiBhQAdHoBzkonVPF0RXigCv5ernxubVB4oDeGdggrntecnJEHN2clmob4omfj8uc183NmOgyiiSpLp5Neaq3XAyaay0YkRWWueJubLWXNSZobN27gjz/+wO+//45du3aZ7DxTp07F3LlzZTueXtDjm1PfIDIqUlT7tiFtsarPKjSr3rx49dzb9/JkWz136tSpmD9/fqWP8yA/Pz/MmDGjVJm2WPz8mkZsSia2nUlEVp4Wfp4u8PFwQYFOQGpmHrLytWge6gcXpYLPrQ0KD/RG3c4qo1bY5ufMdPiMEUmRlyd9KymWaZOVk3rF29xsKWteFm43Upper8fJkyexZcsWbNiwAfHx8SY71x9//IG+ffvKdry03DRM3TMVX578UlT7tx9/G/O7zYe/hz+AwuBn1b44WVbP1Wg0cHNzM/oxGDJo0CC0bdsWoaGh5ZZpi2Xrn19DLPH5Lpr/mq/Vo7a/J1Kz8qFyA9ycneDq5Yq0bA1iUzLh6+GCx2r62exz68icnBRGlV3b++fMkhhEE4n1xRfA6NHG9/vnH6BNG/nHQ2RCUq54m5stZc0fxu1G7svJycHu3buxefNmfPfddyY9V2JiIoKCgmQ73umk0xi5bSSO3joqqn33oOkI9+oHDxcX1PNUIS3TBf4e8qyeu2jRIkyUMpXIgBkzZqBq1apo1aqVqDJtsWz582uIpT7fRfNfa/i5I8DbFVkaLdKyNVC5O8NF6QRXZydcv5uD1nX8bfa5JePY8+fM0hSCYF1psYyMDPj6+kKtVlfqCidRpbFMm8gmPPiDNV9bWJoWHqiyqqz5g0oHTIXb+hT9oHGE7UYSExOxZcsW/PLLL9i7d69Jz5WbmyvbHGBBEPD9me8RGRUJjU5jsH3zoOaY2v5T/BsbUO7r/Ub72th1IQXnE9QlVs8tOl9MShaahvhiRKd6JX7oarVauLiULs+sLH9/f0yZMgU+Pj7o1q0b6tatK/s5HmRrn19DLPn5vpyUgc/2xKBuNRWUTgqkZecjLiUbaTka6P5/nr8CwPs9G6JnY/kuJpH1s7fPmakYE4cyE030oIwMwFfCCqj+/sDdu/KPh4gMsoWseRFH3W5EEAScPXsW//vf/7BhwwZcv37dZOfq3Lkz/vrrL9mOl5GfgY/++gjL/lkmqv2w5sOwoPsCBHoFPrCNk7rc1/vXk7eRkpEnavXcbZu+x8iRI2V7bEWef/55PPnkk6hZsyZ69uxp1iSGLX1+DbH05/vh+a/+Xm6oEuaKzDwtNDo9NFo9tDo9Hg1mksrR2NPnzFowiCa6dAlo1Mj4fsePA61ayT8eshuc82o+xs4TsxRH2m4kPz8ff/31F3744Qds2LDBpOfasmULBgwYINvxzqecx+jto3Hg+gFR7Vc8vQIjWo2As1PJn1ViX2+dICCkSunXW6fT4qP+hXtCL5X4WMrz4YcfokaNGmjVqhWeeOIJ2cq0pbCVz68hlv58lzX/VaFQwMfDpURVA+e/OiZ7+ZxZCwbR5Hj0esDHB8jOltaXZdokAue8UlnsfbuRO3fu4Ndff8WGDRtw4IC4AFSquLg42UqNBUHApgubEBkViYz8DIPtGwU0wpd9vsRTtZ+qsJ2Y11sv6KFUKIqzh4e3rsevK2dLehwVqVKlCiZPngxfX190797d5GXajsjSn2/OfyUyHwbR5BjS04EqVYzv5+kpLdgmhybHIkFUmj1k9u1tuxFBEHD58mV899132LBhA27evGnS8+Xn58PV1VWWY2VpsjBn/xwsOrJIVPvBTQdjcY/FCPYOFn0OMa+3j6sTPnvVNItP9u7dG927d0doaKjZy7QdkTV8vm1ldwUiW2cbf6WJpNi6FZBS3peQAASL/5FE9CBLz4mzV/aS2beH7UYKCgpw4MABrFmzBps2bTLpuapUqYK7d++WKo2V6urdqxizfQx2/Sduz+nFPRZjbNuxcFFKW8CrvNf7SNRG/PLZR5KOaUjTnoNQNTgULVo+jrdfjEDDYD+TnIdKs5bPN+e/Epkeg2iyL1J/aFnXIvVkwyw9J84e2VNm31bLLdPT0/HLL79g3bp1OHz4sEnPNXXqVMydO1eWYwmCgC2XtyAyKhJ3cu4YbF+vSj2s7rsa3ep2k+X8Ra/37fQcvB/xiCzHfJiXyhut+r8Bwc0HLZ54EjVr1y1eDfr7ozcxtIPSZj4fts6aPt+c/0pkWgyiybZJ3YaqRQvg1Cn5x0MOz9Jz4uyNPWb2yyu3bFLDF4+F+kKrF3AzLcfimaO4uDisWbMG69evx+3bt016rqioKPTp00eWY+UW5GLBoQWYc2COqPYvNHoBS3ouQahvqCznL7J792706NFD1mMW6dSpEwYMGIAaNUJw06M+4jL0dvP5sHUspyZrYQ9ToKwZg2iyPT/9BAwebHw/tbpwQTEiE7KGOXH2xF4z+w+XW97JzMfpG+n47dRti5Wr63Q6HDlyBMuXL8evv/5q8vOlpqaiWrVqshzrv3v/4d0d7yLqapSo9vO7zsf4duPh5uwmy/mLNGjQADExMbIes8ibb76Jpk2b4vHHH0e7du2gVCpxMy0HS3ddtbvPh61jOTVZmr1MgbJmRv+KO3DgAD755BOcPHkSiYmJ+O233/DMM88U3z9kyBB89913Jfq0bdsWR48erfRgyUEJAuDkJL0vkRlZy5w4e2HPmf2icsvYlEz8eT7JIuXqWVlZ2LRpE1avXo1jx46Z5BxFfHx8kJ6eLtv85j9j/sTwP4bjdqbhLHlNn5pY3Xc1etfvXXyb/v8z/pUJci5duoRGUrZIFMHVzQ0jx47HI3Vro0eP7qhXr16pNvb8+bB1LKcmS7GnKVDWzOggOjs7G82aNcPQoUPx/PPPl9mmV69eWLt2bfG/5VpJkxxIbm7hytjGWroUGDdO9uEQiWVNc+Lsgb1n9i1Rrn7z5k2sWLECP/zwA5KSkmQ5ZnmWLVuGd999V5Zj5WvzsfjIYkz7a5qo9v0a9MPyXstRp0qdUvdVJksTGhqKW7duSXoMhjR+rDnqP9ETBZ7VUL1RGzj5+EIXoILgHVhme3v/fBCRcexxCpS1Mvpb9emnn8bTTz9dYRs3NzcEBQWJOl5+fj7y8/OL/52RYXh/RrJTt24BoRLmpOXmAu7u8o+HSCLOiZOPvWf2zVGurtfr8c8//2DRokXYsmWLDKOu2OXLl9GwYUNZjnVTfRPvRb+HXy+JKy+f0XEGJj05CR4u5b8fjM3SxMfHo06d0oG4XAYNGoQnnngCgXUewVlNINLz9P8/LmeD2SN7/3zYGs5BJVMS8/6y1ylQ1sgklyb37duHwMBA+Pn5oVOnTpg3bx4CA8u+irpgwQLMmjXLFMMga8cybbJjnBMnD3vP7JuqHDc3Nxf/+9//sHLlSpw8eVKOoRo8n7tMFzP3/LcHkVGR+O/efwbbBngG4Kt+X6F/w/6iysTFZmmGvdAHBw8erPRjKc8HH3yA8PBwdOvWDfXq1YNeL2DVvjikJ6iNyh7Z++fDlnAOKpmS2PcXp3iYj+xB9NNPP40XX3wRtWvXxrVr1zB9+nR07doVJ0+ehJtb6QU8Jk+ejPHjxxf/OyMjA6FSspFkG6SWaU+fDsyeLf94yOLs+co958TJw54z+3KW4yYlJeHTTz/FunXrcOeO4e2cKqN3796IioqSZX5zga4Ay/9Zjg92fSCqfc96PbHi6RVoULWB0ecqL0uj1WjwYd+mRh9PrIYNG+KNN95AeHg4evbsCV9f3zLHFeTjjsw8LTQ6PVyVTvB2dzaYPbLnz4et4BxUMiVj3l+c4mE+sj+DAwcOLP7/TZo0QatWrVC7dm1s27YNzz33XKn2bm5uZQbXZEd27wakbPOh1QJKpfzjIavBK/cklr1m9itTjisIAk6cOIG5c+di69atJh/r1atXUb9+fVmOlZiZiAm7JmDDuQ2i2k/qMAlTO06FylVVqfM+mKU5+ufP2LRU3PxqKfr27YuuXbuiVatWaNeuHZwr2I4xW6PFnax8JKTnIj23AFq9Hs5OTvD3dEW9QC/4eLhUmD2y18+HLeAcVDIlY99fnOJhPia/DBEcHIzatWubbMsHslItWgCnTxvfj2XaDsPYK/f2nLEmcewxs29sOa5Go8GmTZvwySef4OzZsyYfX2ZmJlSqygWuRQ5eP4jIqEhcvnPZYFsfNx+s6bsGLzV+SbbVvPV6PR4N9jXcsBLGjBmDJk2aoFu3bggPDxfd705mPm6m5UAQBPh5ucJF6YwCnR4pmXnIzC9A/UCVweyRPX4+bAHnoJIpGfv+4hQP8zF5EH337l3cvHkTwcHBpj4VWVJ+vrTFvb75Bhg2TP7xkFUz9soqM9ZkzwyV4/o55ePDD+fgm2++QVpamknH8u6772LJkiVwkrpexQO0ei1WHV+FsTvGimrfpsZTmNd5CbrWe1y2H3g7duwwuBhqZQQHByMyMhKNGjVCz5494efnZ/Qx9HoBp2+kw8XZCTq9AFelExQKBdyclXD1csLdrHycv52BAc1DmD2yQpyDSqYk5f3FKR7mYXQQnZWVhdjY2OJ/X7t2DadPn4a/vz/8/f0xc+ZMPP/88wgODkZ8fDymTJmCatWq4dlnn5V14GQF/vwT6N3bcLuH6XTSFxQju2DMldV8rY5zzcjuPVyOG3/lAlZ+Mh2jt0WZ/Nw7d+5EDylTbsqQkp2CibsnYt3pdaLaD3lsFBp7vYWEewrkaXXYfkqJKzfjJF8gEwQBPXv2xO7du43uK1bnzp3Rt29ftG7dGu3bt6+wTFuM2+m5+O9ONprU8EFMSjbSsjVQuTvDRemEAp0eWj2gFwQ8FurL7JEV4hxUMiWp7y+rmuKh1wO//QbUqQO0bGn+85uI0Z/oEydOoEuXLsX/LloU7I033sCqVatw7tw5fP/990hPT0dwcDC6dOmC//3vf/D25o9cm8fVtEkmYq+sZuYX4K9LqZxrRnZPq9Xi559/xty5c3Hx4kWTny8+Ph61a9eW5Vj/3PoHI7aNwOmk0wbbuju7Y03fNXj1sVcRl5qFtYfjEZdSuQtkarVaUgbYGEOHDkXbtm2NLtMWo+j7sG41FbzcXBCbkoV7ORpk5Wvh7OSEIF93uDk7IcCb68dYI85BJVOqzPvLolM8cnOBPXuA338Hvv76/u3r1wODB1tmTDIzOoju3LkzhAoCoujo6EoNiKyM1MD54EHgySflHw/ZBbFXVrPytJxrRnYrPT0d8+fPx+rVq5GRkWHScz3++OM4cuQIXF1dK30snV6Hr099jRHbRohq365mO3zR5ws0D2pefFtlF2Nas2YN3n777Uo/lvJ4e3tj9OjRaN68OSIiIkwapD/4fejv5YrWYVVKrNANCFDnapnJtFKcg0qmZFPvr6NHgU8+ATSawgA6N7d0m6ws84/LRPiNTKWdPAm0amV8P2abSSSxV1ZVbs6ca0Z25fz585g0aRK2bdtm8nO988FUfLZorizHSstNw9Q9U/HlyS9FtR/VahTmdp2LKh5Vyrzf2MVydDpdpcumDXn88cfxwgsvoH379rKUaYtV1vehj0fhxUVBEBCTksVMppXjHFQyJat9f+XlAe3aiV9I+PXXgeHDTTokc2IQTdKzzQ0aAFeuyD8esntir6y6OSs514xsmk6nwy+//IKPPvoIV8zwfTnp2x3wqFYT6TkFeK+H8fsoP+hU4imM3DYSx24fM9hWAQW+6vcVhrYYCieF4b8nYqZ0HD+8D7UGtTB63MZ46aWX0KVLF3Tr1k227buMZVOZJiqXVc1BJbtjNe+vgweBjh0NtwsKAvr2Bfr1A7p1A7y8TD82M+MvT0dVUABIKeu7dQsICZF/PORwxFxZ1esFzjVzIPayjVlmZibmzZuHFStWICcnx+TnWxR1Ds7//31emcylXtDjhzM/YPgfw1GgLzDYvmVwS6zqswptQtoYPeaypnQIgoAFQyNwJ+G60cczRtt+r6Bqnab4eNxraFKnhknPJZbVZprIKNxmjEzJYu+vTp2AAwfEt//lF+DZZ+1+EWEG0Y4kJqYwe2wslmmTiRi6ssoMjeOw9W3MLl26hAkTJmD79u0mP9fSpUvRd/CbxavW5+oV8NDrJX0u1HlqzPhrBj479pmoc7/V4i3M7zYfAV4BlXoMRSXMB0+cwf8mvlCpYxkSGFoXLbr0Qb3H2qBO45YQFE6Iv5MNZw959r+Wi9VkmojIsaWmAoGBxvU5flzaVFAbxiDa3g0fXnJVPDGcnAq3oSIyA0NXVpmhsX+xKZk2t42ZIAj49ddfMXny5BLbPprKjRs3EBoaWuI2qZ+L8ynnMXLbSBy6cUjUuVc+vRIjWo2A0klZqcdQZMqUKViwYIEsxypPWPMOaNSmE5q164SAkLAS92XmFZSYBmJNFRDMZBKRRezYATz9tHF94uMBmXZ5sEUMou2NVgu4lJ47apBaDfj4yD8eIhkwQ2O/KrtKszllZ2dj3rx5WLJkCfLz801+Po1GA5cKvs/Ffi4EQcDG8xsRGRWJLI3hlVEbBzTG6r6r0aFWh0o/BqBw+66KHodchg8fjm7duqF79x7YeCYN5xPUqBZYMtv88DQQW6+AICKSROp6SDqd3Zdpi8Ug2h7s3Vs4ad9YLNMmG8IMTdmsKYsmhbGrNJvb1atXMW7cOPz5558mP9cHH3yARYsWGdWnvM9FZn4mZu+fjcV/LxZ1nFcfexWLui9CsHewUecvz/nz59G0aVNZjlWeGjVq4I033kBERAQ6dOhQYjXtiCYuBqeB/Hcny+YqIIiIJLt0CWjUyLg+EyYUbltFpTCItlXNmgFnzxrX548/ClfKIyK7YA9ZNDGrNJtzGzNBEPDbb7/hgw8+wH///Wfy83377bcYOnSoLMe6cucKxvw5Brv/2y2q/ZKeSzCmzRi4KOXJEo8cORJffiluCyypOnbsiGeeeQZ9+vRBgwrW+DA0DaRuNRVW7YuziQoIIiLJhgwBvvvOuD5XrkhbQ8nBMIi2FVLLLjQaaeXdRGTVbHEecVnKWqX5QebYxiwnJwfz5s3DggULIJihQicpKQnVq1ev9HEEQcDmS5sRGRWJtNw0g+3D/cOxuu9qdK3TtdLnBoCsrCx4e5v+PTZo0CD0798fvXr1QpUqZe87XZaKyt1vpuVYdQUEEZEkOh0gZY97lmkbjUG0Ndu5E4iIML4fy7SJ7JotzSM2pGiVZnNvYxYTE4N3333XLGXaAKDX60sFa1LkFORgwcEFmHtwrqj2LzV+CZ/2/BQ1fWpW+twAEB0djV69eslyrPL4+Phg6NCheOaZZ9ChQ4dKzacur9zd2iogiIgk27bN+ErTF18ENm0yzXgcBINoazN4MPDTT8b1OX26sLybiByCtc8jNoa5tjETBAG///47xo8fj2vXrsk0+vJt2bIFAwYMkOVYcWlxGLtjLLbHiNs+a37X+RjfbjzcnN1kOf+3336LN998U5Zjladly5Z46aWX8Oyzz1ZYpi0Xa6iAICKSTMpFWcYLsuJfB0vT6YC2bYGTJ43rp9dL+wARkc2ztyyaqbYxy8nJwYIFCzB3rrisbWXl5+fD1dVVlmNtu7oNkVGRSMhMMNi2lm8trO67Gr3C5ckQ5+Tk4NFHH8WNGzdkOV55+vfvjxdeeAF9+vSBv7+/Sc/1MEtVQBARSZKdDagk7G3PeMFkGERbwt27hatpnzkjvs+bbxq/3zMR2SV7zKLJtY1ZbGwsxo0bh23btplopPdNmzYNc+bMkeVYedo8fHL4E8zYN0NU+wENB2BZr2UI8wuT5fwXLlxAkyZNZDlWeRQKBd566y0MHjy40mXalWWuCggiIslWrADGjjWuz7PPAps3m2Y8VILt/MKydd9+WxgIG+PIEaBdO9OMh6iSbH1rJVtmr1k0KduYCYKAP/74A2PHjsX169dNNLL7bt26hZCQEFmOdUN9A+9Fv4fNl8T94JnZaSY+7PAhPFwq/7rq9XrMnj0bs2bNqvSxKtKgQQMMHjwYgwYNQsOGDU16LmOZqgKCiEgyKVnjf/8FmjeXfShUMQbRpqLTAV99BYwcKb7Pq68CP/xgujERycQetlayZY6eRcvJycGiRYtMHgACwKOPPorz58/DSaZVS3fF7UJkVCTi0+MNtq3uVR1r+q1B/4b9ZTl3RkYGfH19ZTlWRbp164ZXXnkFAwYMMHuZtrHkqoAgIpIkLQ2oWtX4flxN2+IUgjn28zBC0R95tVoNHx8fSw/HOKmpwOTJwDffiGvv5AT88w/QqpVpx0Uko9JbKzkjR6MtDt5sZWsle/DgxYx8bWEJd3igyi6zaLGxsXjvvfcQFRVl8nPt2bMHXbvKsw2URqfB8qPL8eHuD0W17xXeC5/1+gz1q9aX5fx//vknevfuLcuxKvLyyy/jrbfewlNPPWXRMm0iIqvXsyewa5dxfdq0KYwZyKSMiUOZiZbDZ58B774rru0HHwALFgBKpWnHRGQC9rS1kj2w5yyaXq9HVFSU2cq0ExMTERQUJMuxEjIT8P7O97Hx/EZR7Sc/ORlTn5oKL1evSp9bEAS8+eabWLt2baWPVZHg4GC89tprGDZsmNWVaROZi1zTmjg9ygFIKdOOiQHCw+UfC8mCQbQcYmPLv+/xx4Evvii8gkRk4+xpayV7IWUesbXKzs7G4sWLMXPmTJOf65lnnsHmzZtl2bsZAA5cP4DIPyJx5e4Vg209nH3wcdcVGPPEa7KcPzs7Gyopq7YaqW3bthgyZAheeuklqy/TJjI1uaY1cXqUnYqJAaRs18cybZvBIFoOzz9fuIJekbffBubNkzbHgciK2dvWSgAzAJYWGxuL999/H1u3bjX5ua5evYr69eUpk9bqtfj82OcYFz1OVPs6qjZ4vu4MeDuHIVGdh6QkV8SlZkn+kRwXF4dwM2QoBgwYgNGjR6Nz584s0yb6f6WnNXkgR6PF+QQ1EtS5oqc1yXUcshK9egHR0cb18fQs3L6KbA6DaDl06ADs3g106cKrR2TX7G1rJWYAzE+v12P79u0YPXq0yfchrlKlCu7evStbtjk5Kxkf7v4Q35/5XlT7riHDEOb6OhoHBZUYg9SpDx9//DEmTZokaexi+fj44LXXXsOYMWPQsGFD2Z47Insh17QmTo+yA4Ig7Xf/1auATBd0yXJs45eutXN2Ltz3mcjO2dPWSswAmE9mZiaWLVuGGTPE7YFcGX/88Qf69u0r2/H+vvk3RmwbgbPJZw229XD2xOq+q/HqY6/g1r1cLN11FX6eLpKnPuh0Ojg7m/7PdJMmTfDmm2/i9ddfZ5k2kQFyTWsy1/QoVlvJ7J9/gCeeML4fy7TtDoNoIhLNXrZWYgbA9K5evYqJEydiy5YtJj9XVlYWvLwqvygXAOj0Onx16iuM3CZue8K6Pi3R3v9DeDuHw91ZiYy7KsSlZkGrFyRNfUhNTUVgYGClH4ch3bt3x7hx49CzZ0+WaRMZQa5pTeaYHsVqK5k0bw6cOWNcny5dgL17TTIcsg4MoonIKOGB3hjaIaz4D3NyRh7cnJVoGuJrM1srcYE0+el0Ovz5558YM2aMyVfT7tKlC/bK+OPkbs5dTNkzBWtOrRHVfkzrMRjS9ANsPqEutdVbUSXD002CRE99mD9/PqZOnSrb4ymLk5MT3njjDXzwwQd45JFHWKZNJJFc05pMPT2K1VaVoNdL20Xn/HmgcWP5x0NWiUE0ERnN1rdWsscF0ixBrVZj5cqVmDZtmsnPlZSUhOrVq8t2vJMJJzFi2wicSDhhsK2Twglr+q7B0BZD4aRwgl4vYNW+uAorGc7cTEfdAC9cSMgoNfUhPzcHHw1oAQBYKtsjKi0sLAzDhw/H22+/japc6JJIFnJNazLl9ChWW0lw4ADQqZPx/fR6adtXkc1jEE1Ektjy1kr2tkCaOV2+fBlTp07F5s2bTXqejs++ga5DJkCdq8V7PRqgeiXfa3pBj+9Of4fIqEho9YYvjrSq0Qqr+qxCqxqtSt0nppIhLjUbz7YMQaI6DzEpWVCqb+HzMc9U6jGI0a5dO3zwwQfo27cvy7SJTECuaU2mnB7FaiuRpAS/zz0H/Pqr/GMhm8NfiETkcMRmAIJ93HEzLccms+1yKSgowI4dOzB27FjEx8eb9FyvT1uG5h2fLv63Vq9HSma+5IqA9Lx0TN87HSuPrxTV/q0Wb2HM49PhpvQrfr3LIraSYfnM9/Hrhh8kjd0YL774IqZPn44mTZqwTNvMuGiTOPb2PMk1rclU06NYbVWOggLA1dX4fidPAi1byj8esmkMoonI4YjJADQM8sbqA/855IIsaWlpWL16NaZMmWLyc727/jj8vT1kqwg4l3wOo7aPwqEbh0S1/6L3F4h8PBLX7uQg+nwyvjuUhjxtaoWvd3mVDIIg4P2IR0SPVaqAgAAMHz4c48ePZ5m2BXHRJnHs9XmSa1qTKaZHsdrqAYsWARMnGt+voKBw9x2icvDdQUQOqaIMQMMgb+y9nOIwC7IIgoCLFy9i5syZ+OWXX0x6rrVr12LIkCEAUDy3uDJzAgVBwIZzGxAZFYmcghyD528a2BRf9v0S7UPbF99m7AI8D1YyOOvyMPXZ0iXfcmvatCkmTZqEF154Aa5SMikkmpisKRdtEsfenye5pjXJPT3KnrajlERKRY6fH3DvnuxDsQf2VkkiFwbRROSwysoABPu4Y/WB/+x+QRaNRoMdO3Zg3LhxuHbtmknPpdVqoSxjpVOpcwIz8zMxe/9sLP57sajzv97sdXzc/WMEqYJK3SdlAZ4bN65jTLf6xj4NRuvduzfmzJmDFi1asEzbTMRkTblokzh8nizHXrajFO3ePUDKHvepqUC1avKPx47YayWJHBhEE5FDezgDcDMtx24XZElNTcU333yDyZMnm/Q8n376KcaPHy+qrdg5gZdSL2HMn2Ow95q4ra2WRSzD6Daj4exU8Z85sQvwfDRvIebOMG15u4eHB4YPH45p06YhICDApOei0sRmTblokzh8nizLHrajrNCYMcDnnxvfT6stsX0Vs6zls/dKkspiEE1E9AB7WpBFEAScO3cO8+bNw6ZNm0x6rrS0NFSpUkVS37IqAmr4umPLld/QZu1w3MszXGLXoGoDrO67Gp3DOht17vJeb71ejwVDe+Ju4k2jjmesevXqYfLkyXjttddYpm1BxmRN7ek7wpT4PFmerW9HWYqUipyePYHo6DLvYpa1fKwkMYxBNBFZnDVdCbb1BVny8vIQHR2N999/H3FxcSY7T//+/bFlyxbZyoydnBSo6g18eeBjzD80X1SfQU0GYXGPxQjxCZF83gdfbxd9PqY887jkY4nVsWNHLFy4EE888QTLtB9iqe8CY7Kmtv4dYS58nqyDLW9HiawswFtCMLt3L9ClS4VNmGWtGCtJDOM3FxFZlLVdCbbFBVkSExPx3XffmbxM+8qVK2jQoIGsx4xNi8U7f76DHbE7RLVf2G0h3mv3HlyV8mRtz/69D0sH9ZHlWBV56623MGfOHAQFlZ6XTYUs+V1gTNa0QaC3zX1HWIItfpeSFXjkEeDKFeP7PVSmXRFmWQ1jJYlhDKKJyGhyZYus8UqwLSzIIggCTp06hcWLF2Pjxo0mPZdOp4OTk5Osx/zjyh+IjIpEUlaSwbZhfmFY3Xc1etbrKdv5J06ciEWLFsl2vLIEBgZiypQpGDlyJMu0RbD0d4ExWVNb+I6wBnyezMeaqrmMJgiAlL8xHToAh8RtZfgwZlkNYyWJYY77yIlIErmyRdZ8JdgaF2TJyclBdHQ0Jk6ciJiYGJOd58iRI2jXrp2sx8zT5uHjQx9j5v6Zoto/88gzWBqxFGF+YbKcXxAEBAQE4O7du7IcrzytWrXCokWL0LlzZ5ZpG8EavguMzZpa43eENeLzZHrWVs0lyqVLQKNGxvc7fhxoVfktBZllNYyVJIYxiCYi0eTMFln7lWBrWJDl1q1b+PHHH01epq3X60u8BnJkNa6nX8e46HHYcnmLqPazO8/GBx0+gLuzu1HnKY9Go4Gbm5ssx6rIoEGDsGjRIoSGhpr8XPbKGr4LpGRNreE7whbweTIdS1dwGGXQIOB//zO+X24u4C7P34UizLIaxkoSwxz33UFERpE7W2QLV4LNvSCLXq/HiRMnsHz5cmzYsMFk5zl16hRatGhR5n2VyWpEx0YjMioSN9Q3DI4hSBWENX3XoF/DfpIeQ1nOnTuHxx57TLbjlUWlUmHy5MkYP3483GX+YeeorOW7QErW1KYXbTIjPk/yE/M3Ofp8ElybOSGnQGf+ixdSy7RbtABOnZJ/PA9gllUcVpJUjEE0EYkid7aIV4ILZWVlYceOHZg2bRquSFlMRaSHs81lMTarodFpsPTvpZi0Z5KoMfSu3xvLey1HuH94pR7Lg+bMmYMZM2bIdryyPPLII1i8eDF69+7NMm0TsKbvAmZNyVYY+pvs4eKEbeeScPa2GkonhXnKvI8eBaRMBzp1qjB4NhNmWcXjd2L57PvXKRHJRu5skSNfCY6Pj8fGjRtNWqa9d+9edDGwxceDxFYauLmqMWH3+9h0Qdy+01OenIIpT02Bl6uXpMfxMEEQZF/orCz9+vXD0qVLUa9evUofy6YX/TEDa/suYNZUftbwGbCGMcipor/JadkaXEnOQlp2PhpWVyGkiqfpyrylXljMyQE8LPf3nVlW8fidWDYG0UQkitzZIke6EqzT6fDPP//giy++wPr16012noKCAjg7S/taryirEZdxDD/fmoEv4+Ix+kDFx/H38Meavmvw3KPPyZa11el0kh+XMSZPnoypU6fCy0uegB+w0UV/zMyRvgsckTV8BqxhDHIr72+yIAiITclCVp4Wvh4u8PN0hdJJId9CfXq96K2kSggJAW7dMr6fCTHLSpXBIJqIRDFFtsierwSr1Wrs2LEDs2bNwqVLl0xyjsOHD6N9+/ayHOvBrIZOX4BDSevxe/wCUX271emGFU+vwKMBj8oyFqBw7+saNWrIdryyhIaGYvHixXjxxRdNUqZtU4v+WJg9fxc4Mmv4DFjDGEyhvL/JmXla3MvOhwICqqrc4O1+/6e+5IX6Dh0CnnrK+EEePAg8+aTx/cyIWVaSikE0EYliqmyRPV0Jjo2Nxc8//4wpU6aY5Phubm7IysoySVY2R3sX+1JmYlVslKj2E9pNwIxOM+DtJt+Pzy+//BIjR46U7Xhl6dKlCz777DM0adLEpOexhm2bbI09fReQdXwGrGEMplLe3+R7ORrcyy1ANZUr6gV4lbpAKHrqldQLiwUFgBkqh4gsje9yIhLNVNmih68E6/UCbqblWP0Paa1Wi8OHD+Prr7/Gjz/+aJJzHDp0CB06dDDJsY/cPIK3o97G+ZTzBts6K9zxasN5+PqFcVAq5ZuT/MILL+DXX3+V7XhlGTt2LGbPng1fX1+TnudB1rBtky1iVsh+WMNnwBrGYEpl/U3W6gRU83JFw+re8Pcqvc1fuVOvtFrApfRULVH0eulBtxnY23x4sg4MoonIKKbOFln73LV79+7hzz//xPz583HhwgWTnEOr1UIpZc6ZATq9DmtOrsGo7aNEtQ/zfhxPh0yBUFAb/l6uGNohrNIBtDkWBqtSpQoWL16MIUOGmGURsrJYy7ZNRJZiDZ8BaxiDqT38N9nDRYk/ziTgQkIGBEGoeOrV2rXAsGHGn/Svv4DOneV7ECZk7b8pyHYxiCYio5kqW2SNc9cEQcCVK1fw66+/Ytq0aSY5R3R0NHr27GmSY9/JuYPJuyfj63+/FtX+9aYj0EQ1HIn3nJCv1cENSoSHqEpVGhhzZd8cC4O1adMGK1euROvWrU16HrGsadsmIkuwhs+ANYyhssR81z78N7lXkyAkqvPKnHq16rVW0gaSlQXIuOiiOVjjbwqyH9b7rUFEBtlTidKDc9fCA7yQla/DvRwNXJVOCA/wQmxqttnmrmk0Ghw8eBDr1q0zSZn2wIED8dNPP5lsz+ETCSfwdtTbOJV4ymBbZydnrOm7Bm80fwNOisKsraH3lZgr+wkJCQgJCTHJ4ysybNgwLFiwAIGBgSY9jxTWtm0TkblZw2fAGsZQGVKzqA+Wed+6kYwZQyUs7tW/P/D775UYvWXZ0nx4e/ot50gYRBPZKHsrUSqau+bh4oST19ORlqOBVq+Hs5MT/D1dEeTrZtK5a3fu3MH27duxePFinDt3TvbjX758GQ0bNpT9uACgF/RY++9aREZFQi/oDbZvE9IGX/T+Ao/XeLzM+yuqNKjoyv6RQ/uw4aPhlXosFXF1dcXixYsxYsQIuEidu2cm3LaJHJ01fAasYQxSVSqLOnkywhcuRLixJ926FejXr7JDtwq2Mh/e3n7LORIG0UQ2yB5LlLI1WtzJysfd7HzkF+ihcneGi9IZBTo9UjLzoM7ToKqXm2xz1wRBwIULF/Dbb79hxowZshzzQYMHD8aPP/5osmxzel46pu2dhs+Pfy6qfWTLSMzvNh9VPatKPmdZV/Z/+ewjHInaKPmYhjRq1Aiff/45OnXqZLLn0lS4bZP8ysrYAGAWRyJTZ8Cs4TMgdQyWzA5KyqJK/X5MTwfMuOiiudjCfHh7/C3nSBhEE9kYWypRMoanixJ3svKRk69FoM/9K8duzkq4ejkhOSMPEArbSZWXl4f9+/fjxx9/NEmZdlJSEqpXry77cYucSTqDUdtH4cjNI6Laf9nnS7zV8i0oneRZpOx2ei5iUzLxpdQ5dSINHDgQixYtQq1atUx6HnPgtk3yKStj4+fhAiiA9JwCZnGMZK4MmDV8Bowdg6Wzg2KyqMlX4+HUtb60E1j5atpysPb58Pb6W86RMIgmMgFTXsG2lRIlYwkAAAUElPc8Fd4nGHncpKQkbN++HZ999hnOnDlTqTE+LCIiAjt27JD1mA8SBAHrz63H8D+GI0+bZ7D9Y9Ufw5d9vkS70HayjiM3NxeenqZ9L82fPx/vvvsuPD09iz8/l5My7CLo5LZNlVdWxiYhPQe7LiUDAFqHVUHdaipmcUQydwbMGj4DYsdQ3nNz7nY6rqZkok/TYDwa7GPS76Xysqhvv/gEPNX3jD/gvn1Ap07yDM5GWPt8eHv9LedIGEQTyczUV7BtoURJitwCHaqpXKFQAGnZmv8v53ZCgU6PrDwtVO7OqOrlitwCXYXHEQQBp0+fxu+//45Zs2bJPs7k5GSTLmSVkZ+BWftmYcnRJaLaD2k+BAu7LUR1lbwZ8L///hvt27eX9ZgPqlI9BE9HTkbgo+0wPuKR4h8Jls4AkfUpK2NT+CM4H67OToAgICkjHzWreDKLIwIzYOUr77kp0AlQ5xbg+i01LidmoFGwD8IDvU32vfRgFnVG/ybSDpKZCahU8g7Mhlj7fHh7/S3nSBhEE8nIHFf3rb1ESSovV2dUU7mhmsoViep83MvRICtfC2cnJwT6uCPIxw2AoszHlZubiz179mDjxo1Yv369rON67bXX8P3338t6zIddTL2I0dtHY1/8PlHtl/dajlGtR8HZSfprXFa1xJ9/bkffvn0lH9OQRm07o3/kRASG1oUgCIhJyUL9IJ/iTADnh1FZysrYZOZpcS9H8//fgQLSsjXIzNPCx8OFWRwDmAEr34PPDQBk5BYgNSsfMclZ0Op08PN0gU4vwOX/2rvv8Kjq7H/g7+kzmUmFdDoBQUBEEARUegApYgXdXVnWFVFxZdG1rA1dFXv7oijurrrrz8W1K0UC0kQWlA7SQocUAiSZ3uf+/ohJCJlJ7ty5k5kk79fz8DySuffOZ5LrMCfnfM5RKaP3vnTwINpfdBHE/Rr1PB07AkePtvgy7XDEw578UFrqZ7nWhD8ZIpk01W/3471ESarzX9eAjimwuf3w+APQqpQw6VQ4dMZe53UVFRVh6dKlWLhwIXbs2CHrWsxmM5KSkmS95vkEQcBnez/DHd/eAbPb3OjxPdr2wDsT3sGwTvKU452f7V370evYvuRDWa4bzF1zHoCh/xQ4oK/JBFhd3nqZAGbHKJRgGRuPPwCfPwCNXg1AAbvbB4+/tjM9szihMQMWWvX3xuVVYV9JBSrsbpRZ3fD4A0gxaGDQquEVAtColeiWbJLvfalfP0DKv2OvvQbMmSP9eVuBeNiTH0xL/SzXmjCIJpJJU/12P95LlKQ6/3UdOmNHdrIeKQkaOD1+HDpjR6pBjSzPKcyb9y8888wzEIRwd0eHtmjRItxxR/RGMwGA3WPHM+ufwfM/Pi/q+Ft634KX819GTmKOrOs4VGbFuPHX4PC2DbJet1qbNm2wYMEC3HDDDTVjqM4P2kNlApgdo1CCZWy0KiXUKiW8fgGAAJVSCa1KWXMOszihicmAaVVKWJzeFtOXQCyjVg2PL4Ctx8vhDwg195Reo4Ld44fT60KSQQ2tShn5+5LEjPHfv9mG4YPyWJUThnjYk3+hlvpZrjXhvy5EMmnK3+7HW4mSHI3UAgEBOrUKw7qnY8uxCpyxunCqzI7SfT+jZMcabPn+W1nX7Pf7oVQqGz8wAoXnCvGn7/6E7w6Jaz724BV/w99GPwitSivrOgRBiOprHXzl1XjztVfRv/9lQcdQickEMDtGoQTL2CTq1UhN0KLM6gIEAZnJBiTqqz7SMIvTsMYyYIVlNkAA/rP5BNz+QKvqS5CdpIfbG0Cl04sOqQa4fAEIqPqljaAUYHH5YNSpYNJVTTwI633p0CGgm7Ru2ifP2WveO//QSn6h0RrE22c5Cg+DaCKZNPX+lngpUZKjEdT51zhTegpFOzdg//pvUHJ4n2zr/OGHH3DllVfKdr1gBEHANwe+wcwlM1FmL2v0+FRtO9zY5Sm0SxiEErMLaocWJ865kZcReRBttVqjWpJ+33334ZFHHhE90quxTAD3h1EooTI22ck6nKpwAACyknTwCwKcbh+zOI1oKANWWGZDqdmFrCQ9Uo1aJGjVraovQYnFBZ1GidQEDSocXmjVSigUVdsH/AEBeo0SKqUCNrcfSQZl4+9LUvcnv/suMHNmzV/bS7sKNQPx8lmOwsdPI0QyicX+lliXKMnRCOpASSWe+3AJdm9cjZ1L/4VAoOHu2+EIBAJBM6NycnqdePHHFzFv3TxRx/dtk4/exntxWW63OmuTY9/v0aNH0aVLl7DPE0Ov12PBggW49dZbYTDIn91rDvvDojm6jhoWKmOTf3EmBFTNiT521s4sjkjBvp9alRIQgKwkPfp1SGmVfQnsHh+0aiUu65CKY2cdKLe7oQDg8vqRYtAgJUEDly8Ajz8Q/H1JEACpVT+lpYDIX0pSyxLrz3IkDYNoIpm0tv0tkTSCslgsKCgowOeff4HFi/8j25q2bduGfv36yXa9UI5WHMWcFXPwzYFvRB3/zIhncP+Q+3HGEsBrKw8iJUEj277fzZs344orrgj7NYgxYMAAvPLKK7jyyiujXvoe7///cPRW7IXK2ADgLzckuPD7aXF68Z/NJ5Bq1LbavgTVFTF6jQoDOqXC6vL92p3bCl9AQEAAlAoFPL6qrH2aUYvJtiNQqqSVacPnA1QqeV8EETUJBtFEMmpN+1vCbQR1+PBhLFmyBP/617+wbds22dbRFNlmAFheuBwzl8zEKcupRo/NSczBuxPfxcTudcdF2T0WWfb9vvHGG5gTpY6sQ665Gf96cz66do1ORrsh8fr/D0dvxY9QGZuWGtRF2/nfz/2lFrj9ASSEKE1uDX0Jzq+I6ZZhQpJBgySDBqkJGhw6bcPxcgcS9Wq8dLPEX9Z++ilw443yLpqIYoJBNJHMWsv+lsYaQWlVAo7u+Rnz1r+Pf7+3EF6vV5bn3blzJy655BJZrtUQt8+NV//3Kv66+q+ijp/YfSJeH/s6uqZ1DXlMJPt+b7vtNvz73/8W/wLCMP6Oh5E1YByy09MwY2gndI1hQBhv//9w9Ba1FuxLELoiRqNU4D+zhki76OHDQJS22RBR7LTcd0KiGGoN+1uCfeByWM04sGUDdm9chR3rlsn2XCfO2Zvk+3nSfBJzC+bis72fiTr+sasewyNXPYIEjbi1hbPvN5odtbt0646xMx6EpsMl8EEJnVqFvAyTrNneSPYPR/v/n3DWxtFb1Fo0h74ETaG6ImbHf7/Djb+7WdpFWKZN1OIxiCYiSao/cG3YuhP2wp+wbc0SFB3aK8u1n/tyK3QJRhSW2aL+oW3N0TWYuWQmDpUfavTYtgltsWjiIkzpMUVSCXlj+34T1QHcM7Ib7pHyQhoxbdo0PPbYY7j44ouhUCii2iQrnvcPh7s2jt6i1iLe+xI0iV/f1/N+/SPan/8MvPpqNFZERHGKQTS1aOymKz+v14sffvgBS5YswVtvvw2P2x3xNYfceAcuufbOOh/aTvzatEXuD21evxdvbn4TD6x8QNTxo7uMxv+N/z/0aNtDlue/cN/v0ZPF+OCefFmufaFnn30Wt99+e9AxVNHK9sbz/mEpa2OJK7Um8dqXIGoi6aZtsQCJLez7QUSi8V99anGqA+d9pRZsOVqOM1Y33P5ATcZpTK8MGDRqBtZhOHfuHJYtW4Zvv/0Wn376qSzX/NNHP8ELJfRqFVISNIBQNaYmGh/aSm2l+MvKv+CjXR+JOv7BIQ/i8WGPw6Q1RfzcwZgCdsweJbGbawPat2+PV199FRMmTIjKGKrGxPP+YalrY4krtTbx1pdAduvXA8OGSTs3EJA++5mIWhQG0dSiVJdqbj9ZgYOnrfD5BWQn63FRViL0GhU2HTmHgr2lSE/UQatWxlWZaTwRBAF79+7FkiVL8N///leWbtorV65Ep0sG1WQC2yTpkaBVw+HxocTsQmqCFtddlov0RJ0sH9o2nNiAO5fcib1nGi8xN2lNWDRxEab1nha1Tt8//fQTBg0aJPt1J02ahMceewwDBgyI+hiqxsTz/mGpa2OJK7VGLa6vh9T39VdfrSrVJiK6AINoajGqSzXP2dyosHugUSqRmqCC2enF7iIzOrc1osLhwRmbG2qVAld0bgOn1x8XZabxwO12Y926dVi2bBkWLVoEp9MZ8TXPHz8VCAhYuPZwg5nA3afMmDWsq6SAxB/w450t72D28tmijr+649V465q30Dujd9jPJdbixYtxyy23yH7d2X/+C/48+y506dJZ9mtHIp73D0eytlZX4krU3AUC0ht77dkD9Ool73qIqMVhEE0twvmlmllJehw750CiQQOduqrz8DmbGztOVEKjViIrSQe72w+Hx48kQ+zLTGPp9OnTWLZsGZYtW4bPPhPXkboh+/fvx0UXXRT0sWhkKc/Yz+DhVQ/jnzv+Ker4+wbdh6eGP4VkfbKo46V48skn8fTTT8t6zeSUFEya+QiSegyGoE2ARq3C8mN+jDVZ4yqAi+f9w5GurcWXuBI1d6+9BsydG/55SUnA2bOApv77AhFRKAyiqUU4P0Bz+wLw+QPQ6Ktub4VCAa1GhTM2J9qlGKBVq+DweODxB2oeby1jagRBwM6dO7Fs2TJ88cUX2Lp1a0TXmz17Nv7v//5P1LFyZSl/LvoZs5bOwraSxkvMtSotFk1chN/1/R2UCnGlzg01owv12LBhw7B+/XpR1xdr+PDhePzxx5F90aX46KcilNs9yEyuLYGPxwqKeN4/LMfaWlyJK1EIzaYpp9Qy7dtuAz78UN61EFGrwiCaWoTzAzRB8EGtUsLrF6BTV/0Dq1Qo4A8IUCgBrz8AlVIJrao2qGrJY2qcTifWrFmD7777Du+//z5sNltE13O5XNDpdGGfJzUTGBAC+Me2f2Dmkpminmdg7kAsnLAQl2VfFvYaGxp/BKDmMYfbjXenXxH29Rtz3333YebMmejZs2fNGKrGSuDjqYIinvcPx/PaiOJJPI+og98PqCV+dN23D+ghz5QFIiIG0dQi1A3Q1EhN0OKM1QWtUVsVjAgCVEoFAgHA5vUhI0mPRH3t7d/SxtQUFxdj2bJlWL58Ob744ouIrrVr1y706dMnrHOCZTHCyQRWOCvw2OrH8PaWt0U936z+s/DsqGeRZkgLa53na2j80b5SC/w+L96ROXDWaDR47bXXcOONNwYdQxXPjbpCief9w/G8tnjXbDKTFJG4HFH3xhvAnDnSznW5AAm/9CUiakzLiBio1Ts/QOuWYUJehgk2tw/ldg+MOjXcHh9MOhXK7R6kJ2rRNd1YE5TEusxUDoFAANu2bcN3332Hr776KqIy7XHjxmHZsmWSu1Q3lMVoKBPoVR7Bewdewj3rfxb1PIsmLsLtl90uuky7IaHGHyk9NrzzO3kD58svvxyPP/44Ro8e3egYqnhu1NWQeN4/HM9ri1dxnZkk2cTViDqpZdqzZwNvvskxVEQUdQyiqUUIVqrZOzcJB0utKDG7oFYp0LGNsaaZmEalhC8QCKuUM94yMXa7HatWrUJBQQE++ugjWCwWydc6e/Ys2rRpE/GaxGQxqjOBh8qsWH/qW6w98yz8gqfRa1+adSkWTliIK9rJX0Z9fsa35NhBvHznZFmvf/vtt+POO+9E//79wxpDFUkzrFjfr/G8fzie1xZv4jIzSVER08qXSMq09+8HQjS0JCKKFgbR1GJcWKrp9vnRIS0BAzqloX/HVPTMToLT48fKveGXcsZLJubEiRNYvnx5TcZZqn/84x/4wx/+IN/CIC6L8fXOQzjp/xBvbH5D1DX/cOkfMH/0fGQYM2Rd64WWLV+G1357k6zXfOGFF3DzzTejU6dOkq8htRlWvNyv1LzFVWaSoq7JK1+efhp48klp5zqdgF4vzzqIiCRgEE0tiphSzbyM8Eo5Y5mJ8fv9+Pnnn7FixQp888032Lat8Y7Uofh8Pqikzs0UIVQWo9RRiM+PPI3Dlp+Aw41f581xb+Kuy++CWhndt6cPP/wQv//972W7Xl73HvjbU09i/PjxSE6WZ4SWlGZYzBzGp+rKAKvLC5vbB5NejUSdJuYVLQ1pjnvySbomGVEntcz6ppuATz5hmTYRxQ0G0dTiNFaqGU4pZywyMRaLBStXrsSqVavwn//8B2azWdJ11q9fj6uuukqWNYlRncUwaPTYfnYZPj38OFz+xjuBX5x+Md6Z8A6u6hj9td5333148803ZbvepcOuQfuhkzFm+NW4Z1SPqARD4TTDYuYwPlVXBmw/WYET5xxwev0waFXokJaAfu1T47ZCoLnuySdpojKiLpIy7c2bgYEDpZ1LRBRlDKKJGtBUmZgjR45g+fLlKCgowDfffCPpGh07dsTRo0clNwSLhN1jx5s/P4WFh14FDjV+/K19bsVLY15CTmJO1NfWuXNnHDt2TLbrDZs2CwNGTEBiVieUWtxIM2oxvm+7qAalYpthMXMYf6orA06UO3DG6oI/EECiXg23N4CT5Q64vYG4rRBokswkxQ3ZxsC9/TZwzz3SFuH3A2H0jSAiihX+y0cUQiAg4PAZG8psLph0agiCAACwunzw+APQqpQwaJVw+/xhZ2J8Ph82bdqElStX4ttvv8X27dslrfHUqVPIzc2VdG6kDp47iHuX34uCwwWijh/cZg5u6TkT94yITsb2fHL+IiE1Iwd/efivGDFmHLaWVd0TTp8fAaevSUcjiamgYOYwvlRXBpyzeeDzBeDzC2hj0kGhUMCkE1Bu98AXCOCczR2VCoFIm8tFJTNJcU3yGDip77mJiYDZzDJtImp2GEQTBVFdfrmrqBJHy+woqXT9+iEScHkD8PkDUKuUMGpVSDVqRWViKisrUVBQgO+//x6ffvopKioqwl7XK6+8grlz50p5SRETBAFfH/gad3x7B846zjZ6fKq2HW7s+hTaGQbVZDHG94lOxtbn80GjqZ8pk2rU2PG44Te/x+iRo9A1O61mzQPjrEP7hZg5jC/VlQFJejWOnbPDpK8NRBUKBUx6NSocXrRLNcheISBHcznZMpPUrIiqfPH5AKnvuT/+CAwZIs9iiYhihJ+kiC5wfmOmnGQDzA4vTpTbccbqBgDkpBiQatTC6wvgVKUTvoAAp8cf9FoHDx7EihUrUFBQgCVLlkhaT7QbgjXE6XXi+Q3P4+n1T4s6/saLb8S9lz2F3ce1VR3SvX5UCt6oZGytViuSkpJku97999+PqVOnNjiGKt5HIzFzGF+qKwOS9Br4AgFoVHX/ydWolLC5fVApFXB4fLJVCMjZXE5yZpKataDvdS+9BDz4oLQLVlYCMjVcJCKKB2EH0evXr8dLL72ErVu3oqSkBF9++SWmTJlS87ggCHjqqaewaNEiVFRUYNCgQXjrrbfQq1cvOddNFBXBGjPlZRhx9Jwd/oAAlQKwurzQq6s+/KabtEgyaLBq32nkZZjg9/uwYcMGfP/991iyZAl27twZ9hp27dqFPn36ROHViXOk4gju++4+LDkoLuh/duSzuH/w/dCpdTVfu7JzdDK2hYWF6N69e8TXAYA2bdrgiSeewOTJkyMaQxVPmDmML9WVAYGAALVSCa8/AJ269hdiXn8AaqUS/oAgW4VANJrLid2TTy2Q1DLrWbOAhQvlXQsRURwJ+19su92Ovn37YsaMGbjhhhvqPf7iiy/i1VdfxQcffIDu3bvjmWeewZgxY3DgwAEkJvI31hTfgjVm0qhUSNCqoIACbp8fFqcXerUKmcl6dE03wmu3YMkXn+KH9w+iYOk3KC8vD+s5x40bh+XLl0fj5Yi2vHA5Zi6ZiVOWU40e2y6pHd6d+C6u6XZNyGOkZmyD7eEsKFiB8ePHh32tYIYPH45Zs2Zh3Lhxso2hijfMHMaP6sqA3UVmpBo0OGNzQ2tUQqFQQBAE2Fw+pCfqYHX5cEm7FFkqBKLVXC7eqzBIJh4PoNM1flwwixcDU6fKux4iojgVdhA9fvz4kB9oBUHA66+/jkcffRTXX389gKpZrJmZmfj4449x5513RrZaoigL1pjJ4w9ApVCgXaoeHp+ACocb2TgH29at+Gzbj9j/8/qwn8dsNstaihwut8+Nlze+jMfWPCbq+EndJ+H1ca+jS2qXqK3p/D2ch3dtxjfPzZLlunfeeSemTZuGoUOHyrpvOp4xcxgfzq8MsHuqyrbP2dzQaVRwewNQq5VQK5VoY9LJViHA5nIUtscfB555Rtq5LNMmolZK1j3RR48eRWlpKfLz82u+ptPpMGzYMGzcuDFoEO12u+F2u2v+brFY5FwSUViCNWbSqpRQCj4U/7IDZwu3omT3RmwoORLWdZcuXYprrgmduW0KJ80nMbdgLj7b+5mo45+4+gk8fOXDMGiiv3/2UJkVt9/3CNYvfivia+n1ejzxxBO49tpr0bNnz5iM/IoHzBzGh/MrA7afrMCJcgesLh8StCq0TzXgsg6pslYIsLkciRLJ+6LPB8SoTwcRUbyQ9V/R0tJSAEBmZmadr2dmZuL48eNBz5k/fz6eeuopOZdBJNn5jZkEpxkHt25A4Y7N2LlhJTwOa1jX8vv9IRtURVt1WfSqI6sw74c5OGE52ug56QnpeG/Se5h80eSggWek43KCmTBhApYtWxbRNQBgwIABuOuuuzBhwoR67z+xJvb7Fo3vL8WH8ysDrC4vbG4fTHo1EnUa2X/ObC5HQUVSpv2//wFXXCHveoiImrmo/Cr6wg/ggiCEzAY98sgjdUb2WCwWtG/fPhrLImqQIAjYs2c3Tv2wBCu+WoqjOzaGdX6sG4IBgNfvxePfv4gX/ieuTLu94QqMyn4YA3J7NTj6Ro5xOdV69OiBAwcOhHVOML/97W8xdepUjBo1CgZDfAYEYr9vcn5/KT41VWUAm8tRjRdfBB56SNq5NhtgNMq7HiKiFkTWIDorKwtAVUY6Ozu75utlZWUhs0M6nQ46qb8dJYqQy+XCmjVrsG7dOnz77bfYu3ev6HOTMnIxf/HamDdrKrGW4IGVD+Dj3R+LOn5w+u242DQdHVLTkKBVNzr6Ro5xOXKVVD/66KO49tprGxxDFS/Eft8OlVnxzw1HUVTpRGqCFm2NOqiUkDSOiAhgc7lWTep77YABwKZNLNMmIhJJ1iC6c+fOyMrKwsqVK9GvXz8AgMfjwbp16/DCCy/I+VREkpWUlGDFihVYu3YtPv/8c9hsNtHnbi08ifS0tJiX3P5w/AfMXDIT+8/ub/RYvcqEG7s8jQTfVXB4/DDqVOiemShq9I3UcTmCIMgS5GZ26IrLxt2M7N5XYt5vhjebPb5iv2+d0oz4eNMJbDleASWAogon1ColUhO06JpuxDm7J+xxREQAm8u1Gl4voNVKO3f+fODhh+VdDxFRKxF2EG2z2XDo0KGavx89ehQ7duxAWloaOnTogDlz5uC5555Dt27d0K1bNzz33HNISEjArbfeKuvCKX7JsbdTzv2hgiBg27ZtWL16NQoKCrBq1SrR517/5+cweOz1cHh8KDG78PnuCswYmoweWU3bWdsX8GHhzwvxp+/+JOr4rkkDcUOXJ5CV0K3ma8WVTuwtseCKLmmiR9+EMy4nK1EDrdQPc+fpPWQ0+g2fgB6XXwV9ggmFZbZmt4ezoe8bAJh0amw9Xo4P1Eqs3n8aAhRINWqhUSng9Qs4Y3XB5vahW4ZR0jgiIoDN5Vqs2bOBtyQ2YSwuBs6rFCQiImnCDqK3bNmCESNG1Py9ej/z9OnT8cEHH+DBBx+E0+nE3XffjYqKCgwaNAgFBQWcEd1KyLG3U45rOBwOfP/999iwYQO++uorHDx4UPRrWPB9IfYUm8PKvEZDmb0MD616CB/s+EDU8bf1uRtq283omZkFVZC1qZQKeP0BqEJkiIONvmlsXI4aPrw2rR9eE7XC0KbfcRd87QcgoX0vtGtjqtnDWVhma5Z7OEN938rtbhwus+Os3Q2L04sDpVZUOr3o2CYBOnXVz0WnVkBr1KLc7kFRpQttjBqOIyJq7SLZEiMI8q2DiIgASAiihw8fDqGBN2SFQoF58+Zh3rx5kayLmiE59s5Gco2TJ0+ioKAA69atw0cffdTgfXq+U6dOITc3t+oa5Q68tvKgqMxrNDI8m09txqyls7CjdEejx+rVeiyauAi/veS3UCgUNWsPNdrGHxCgUSnhDwSCXi/Y6Jtg43KcNgsevf5yaS/wVx07dsSsWbMwefLkmjFU5//ypNTsgl8QkJ2sx6iemejS1hTR8zW1YN+3crsbO05WwunxQ6tWIkGrgtvrhyAApWY3clOUMGir9iMqFAqY9GqctbmRYtBwHBFRa+N2A3q9tHMXLgRmzZJ3PUREVAc/mZEspO6djeQagUAAP//8M9auXYsVK1ZgzZo1otY6d+5cvPLKK0EfayzzGixbGwl/wI+/b/s7Zi0V94HninZX4O1r3ka/7H71HmtstI3V5UOnNkZYXb56HfNDjb6pvuZPew/jX/eOi+CVAmPGjMG0adNCjqGq3sO58fBZrNpbhhKzE6ctLny5rQi7TpqbVafqC38WAHC4zA6nx4/UBA0qHF4k6jVQAEgGYHb6UG53I0djqPm5qJUK2N0+5KQYmlUpOxFJ9PLLwF/+Iu3coiIgJ0fe9RARUUgMoluhaMyjDWfvbKgMrphr7D1+Gn//988o3LMNn376acj54xcKBAKiOkQHyyCeL1i2NlzlznI8+v2jeGfrO6KOv3vA3fjbyL8hzZDW4HGNjbZpY9LipgHtsHp/majRNyUlJciJ8EPZH//4R0yZMgUjR44UNYbqyFkblu8pRbndg9xUg6ju4fHowp+FSafGWbsbWrUSFQ4vDFo1urQ1Yl+pFRq1Em5fAJVOLxINVb8w8voDqLB7YNCoMKpnRrMqZSeiMERSpu3xAJr6/04REVH0MYhuZeSeR1sdkO8pNqPcUVWCHYyYDG7IfaSlp3Bg648o3PUTdqxZImpdxcXFdcasidVYNjdYtlaMbSXbcNfSu/BT0U+ijn9v0nv4Q78/QKkIr8O1mNE2HdskhHzcV14ERWbPsJ7zfIbEFAy79lbc8dubMGXM1WF16JajmiGenP+z2HaiHBanF8kGDTKS9OiabkJqgganLW6UWV3IStajtNIFp8cPnz8ApUIBnVqFK7u1xZCubWP9UohILoGA9DFSH30E/OY38q6HiIgkYRDdisixZ/nC61UHY+WOqoZJVqcXF+ckIc1Yd/a3mAxudRbY5nSj/NgvOLxrC/Zv+QFHdv/c6Fr++te/4tlnnxW99lAay+aKbXIVEAL4985/Y+aSmfD4PY0+72XZl2HhhIUYmDsw4tfQ2GibCx/fsWkDbhk5QfLzZeZdgstGTsClQ0ZBn5aFErMLWx1aXHLWHtb9JEc1Q7yp/l5vOZ6Kd9cdQZpRg+zk2pLtrhlGWN1eWJxepCRo0LddKgIQUOHwoF1KAm4d1KFZ/MKAiBrw9tvAPfdIO3fHDqBvX1mXQ0REkWMQ3UrIneW7MCDPTtbD6vThVKUTbp8f/Tqk1gTSYjK4ZrMZG1euwM7PVmDTyq/hMJ9rdA0+nw8qqb/Rb4CYbG4wZpcZT6x5Am/+9Kao57m93+2YP2o+0o3pci4fQOOjbb799htMmTJF8vVvueVW6LsOBNpfit6dsuoEvVKzxk29H72pKJUKDOiYhp87VGBPsbnOY2lGHfq2S8ZPRyugVinh8vmg16gxqHObBu81IopzkZRpu93SZz8TEVGTYBDdSsiZ5QsVkF+ckwy3L4AzNjf2llgwqHMbuLyhM7iHDh3CypUrsX79eixevLjR13D7K//Fw78d1ySBRWPZ3Gp7yvbgnmX3YP3x9aKuu2D8AswaMAsqpfzBf2NeeeUVPPDAA5LOTUhIwKxZszBp0iQMHToUpVYvXlt5ECkJGtmyxk2xHz1WGqpwOGf34vJOaRjXJwvpiTrZ+hQQUROKpEx72jTg448jC7yJiKhJNb9PoySJnFm+UAF5mlGLfh1SsbfYjDKLG/tKLEhN0NZkcDum6rFu3Tps2LABy5Ytw8aNGxt8nva9BmLSI29Dp1YhL8PU5Jm5YNlcQRCweM9izFwyEzaPrdFr9ErvhXcnvouhHYZGa5kN+s1vfoOPP/5Y0rmXXnoppk6dWmcMVTW7xyl71jha+9HjhdQKByKKU//+N3DbbdLOLSsD0uWvQiIioqbBILqVkDPL11BAnmbUYlCXNOwrseDmy9ujncGPXZvW461vfsbrr7/e6LU9Hg80Gk1UOohLZfPY8Ld1f8OLG18UdfxvL/ktXhz9IrITw29sJoeePXti//79ks697rrrMGnSJFxzzTVBx1BVi0bWWK796PFMbIUDEcWpSLLFfj8QRrNFIiKKXwyiWwk5s3wNBVCCIODkkUIc3/I/vPX1QSz9+osGr/Xpp5/ixhtvrPf1xvb0RtuBswcwe/lsrDqyStTxr+a/itkDZ0OjavpxI4IghNUF+3wKhQKzZs3ChAkTRI+hAqKXNW4N2dpY39tEFIZIyrSffRZ45BGWaRMRtUAMolsJObN8FwZQfp8XR3ZvwbG927F19Tc4c+pYg+cLgiDTq5KPIAj4cv+XuOPbO1DuLG/0+Ly0PLw78V2M7DyyCVZXXySBc48ePTB16lRMmDAB/fv3l3SdaGaNma0lopj69ltg8mRp565eDYwYIe96iIgo7iiEOItoLBYLkpOTYTabkZSUFOvltDjnj6Vy+/yS9xtv3nsUzy1ajCN7d2LPyk8aPHbP0WKo9Ma4C4YcXgfm/zAfz/zwjKjjb+51M17JfwXtktpFeWXBBQIByd3Ix44di4kTJ2LixIno1KmTbGuS636KRDyV/hNRMxVJtthuBxJYXUJE1NyFE4cyiG6FpAQdgiBgz549WLNmDZYtW4YVK1aEPHbBPz/CPTN+UyfAcvn80KtV6JpuwtjesSvLPVJxBH9a/icsLVwq6vjnRj6HuYPnQqfWNX5wFHi9Xmgljjr5/e9/j/Hjx2Ps2LFITk6WeWW1YhnExuM9RkTNgCBI3588ZgxQUCDveoiIKObCiUNZzt3KhBPwuFwurF27Fps3b8a8efNCXjM1rQ02/nKkzvUunCOdoDXA4fFhT7EZxWYnZgzt1GRBztKDSzFzyUwUW4sbPbZDcge8O/FdjMsb1wQrC87pdCJBQlajffv2uOWWWzB+/HgMHToUGk3T7M+O1R7fWN5jzH4TNUM//wwMHCjt3G3bgH795F0PERE1WwyiWxExWbvS0lKsWLECP/74I957772Q17JYLEhMDB6ghJojnajXwKRTo7DMhoJfTqNLW1NUAg+3z42XNr6Ex9c8Lur4yRdNxutjX0fn1M6yr0Uss9mMlJSUsM/r2mcAbrjuWkyfen29MVRyiceAMZb3GLPfRM1IJO+JFgsQ4t85IiJq3RhEtxKhsna7iyqxbfs2ZDmO4ON/votjx44FPf+FF17Agw8+KOq5Qs2RBqq6QWcn63GozIaiSqdsGcwT5hP484o/44t9DXcDrzZv2Dw8OPRBGDSxmzlcVFSEdu3C31/d+6pxuPjyq9Gx7xBYlSaojVpo27aPSgAdrwFjLO4xILbZbyISIZIy7ZtuAhYv5hgqIiJqFIPoVuDCrJ3X7cL+nzbg+L4dWPWfdxo4LxB2YBYICDh8xoYzNhdMOjUEQah3DYNWhdMWF+wen6TXU23l4ZWYuWQmjlUea/TYDGMG3pv0HiZfJLHjqkz27t2LXr16hXVOeno6Lr5yHBK69MewYcOh1dcG/lmCELWsazwHjA3NKgfku8fOF+sKCyIKYfdu4JJLpJ27cSMweLC86yEiohaPQXQrUFTpxI79h3Fm/09YveE7HNy+MehxOwtP4JK89pKfpzpruetUJQ6fsaO40oXMRD26ZhiRZqxtzOX0VHVxNmrDu/08fg/e2PQGHlwlLiM+Lm8c3hz3Jrq16RbW88ht9+7duCTMD3j9+/fH5MmTMX78eGR07ok3vj+ElAQNtBfM5Y5W1jXeA8aGZpUD0u+xhsQq+01EQURSeXPuHJCWJt9aiIio1WEQ3UIFAgFs2bIF69atC1mGPXXusxg07kb4AgEcO2uH1iS9g/P5WcucFD3MTi9KzC6ctjhhdXtxafsUpBl1EAQBJWYX+uQmIzel8VLqYmsx7i+4H4v3LBa1jkeufASPXvUojFqj5Ncihw8++AAzZswI65zJkydj3LhxGD9+fJ0xVPtLLU2edY33gPHCWeXnrzHce0ysWGS/iehXkZRpX301sGYNy7SJiEg2DKJbEJvNhpUrV+Lbb7/F+++/X+/xLn2vwOyXPqz39UizdsGylt0yE2H3+OHw+GBxelFYZkPPLAVKLW6kGbXI75UZMoO5/vh63LnkTuw/u7/R507Rp2DRxEW48eIbo7InOBzPPPMMHn9cXDMzANAnGHHt9TfhhsnXID8/P+QYqlhkXeM9YFQqFRjbOxPFZicKy6qCfYNWBafHjxKzq9F7TIpY/ByIWrVIuml/+SUwZYqsyyEiIqrGT3vN3PHjx7FixQrceeedQR+32+3Q6w1YuPYw9hSb6+1RliNrFyxrmWbU4tL2KThUZkOZ1YWT5Q4kGzTo2y4F+b3qNqXyBXx466e3MGfFHFHPN6LTCCy4ZgEuTr9Y0nrldN111+Grr74SfXx6+67oM2QUOlxyBTQ5FyM9OQH9hnZCcnLovcWxyLo2h4AxLyMRM4Z2qml8dtrigk6tQp/c5Hr3mBxi8XMganXS0oCKCmnnOhyAgf//ERFR9DGIbmb8fj82b96Mr7/+Gi+++GK9xxcuXIhZs2bV+3o0s3ahspZpRi0u75SKCocHx87ZccvADri6WzqUSgXK7GV4aNVD+GDHB6KeY+4Vc/Hk8CeRpGt48HlT0Gq18Hq9oo+/6LIhSLtoIK4cMRpZHfNqgi9BZFOwWGRdm0vAmJeRiC7DTU0ygisWPweiFi+SMm0A8PkAlUq+9RAREYnAILoZsFgsWLFiBaZPnw6n01nnMYPBALvd3mgpczSzdg1lLRUKBTQqJdJNepj9e9Fv0X3YdXpXo9c0qA14b9J7uLXPrTEv0wYQ1hq0Wi1uvvlmjB49Gn0GXY2PdpqRkqAJ+r0Ru7e4qbOuzSlgVCoVTbYvu6l/DkQt0sGDwEUXSTt36VLgmmvkXQ8REVGYGETHqcOHD+Ozzz7Dww8/XO+xysrKkPtnGxKtrF2orGVA8ON/pf/F50fnAQBea2SL85D2Q/D2NW+jb1bfiNYjl3AC506dOuG6667DqFGjMHLkSBh+LSmsagpWHtbe4kBACPozasqsK8CAMZSm/jkQtQiR/DL0yBGgc2f51kJERBQhBtFxwufz4ccff8T111+P8vLyOo89//zzeOihh2R5nmhk7c7PWu4uOYXdtnex9eynos6dfflsPD3iaaQaUmVdk1ThBM6DBw/GhAkTkJ+fj/79+0MZpCQx3L3F1WPCDp+xweXzQ69WoWu6CWN7VwWtTZl1BRgwhtLUPweiZklq4HzddcDnn0cWeBMREUURg+gYqqiowMcff4zZs2fX+Xq7du1w4sSJqJcxh8p4hmtr8VbMWjoLW4q3NHqsUqHEoomLMKPfDCgVsR83IghC0OA3lBtuuAGjR4/GuHHj6oyhCiWcvcXnjwnLTtYjQWuAw+PDnmIzis1OzBjaKSbZXwaMRCRKRYX0+cuPPgo884y86yEiIooSBtFNSBAEHDhwANOmTcPOnTtrvt6lSxfs3LkTJpOpydbSWMazIQEhgA93fIiZS2bCF2h8xNGAnAFYOGEhBuQMkGv5EQkEAlCJbESTnZ2NKVOmYMSIEQ2OoQpF7N5iAPXGhAFAol4Dk04tqgEZEVGT+81vgI8/lnZuURGQkyPveoiIiJoAg+go83g8WLFiBe6//34UFhbWfH316tUYMWJETNYkJeNZ6arE46sfx4KfF4h6jj/2+yPmj56Ptglto/ESwubz+aDR1C+nDqZv376YNGkSRo0ahaFDh4o+LxQxe4tPljvqjQmrFk4DMiKiqIukSsrlAnQ6+dZCREQUAwyio+Ds2bNYvnw51q9fD5/PB4/HgzfeeAPjxo2LeafpQEAQnfH85cwe3L3sbmw4sUHUtd++5m3M7D8TKmV8jBvxer3QarWijh0/fjzGjBmDsWPHomfPnrL/nBrbWxxqTFi1YA3IiIiahNkMpKRIO3fpUmD8eO5vJiKiFoVBtAwEQcAvv/yC5cuX4/Tp00hMTMTo0aMxbdq0iLOYciuqdIbMeALAGf8q3PfDPNyz3tXotXpn9MY7E97B0A5Do7FUSdxuN/R6faPHJSQk4Oabb8aIESMwbtw4ZGRkRH1tDe0tDrcBGRFRVP3xj8A//iHt3GPHgI4dZV0OERFRPOEn8ggUFhbi66+/htfrRbdu3XD77bcjTWpTlSZyYcbT5beh4ORbWFv8T1Hn39b3Nrww+gVkmbKiucyw2O12UfvJ8/LycN1112HYsGF1xlDFg3AakBERRYXUbLHRCJw7xzJtIiJqNRhER6Bz5864//77Y16iHQ6jVg27/zje/uVFHLVuFnXO62Nfxz0D74FaGT+3S2VlJVJTGx+LdfXVV2P8+PEYNWpUyDFU8UBsAzI2FSMi2bjdgIjKnaCmTatqKNaM/v0jIiKSS/xERc2QWt08vn2CIOCLfV9g5pKZKHeWN3p8W30nvDTq/zCqy8i4mglcUlKCHBGdXKdOnYoRI0Zg7Nix6NSpU80or4NltriecyymARkRUURmzwbeekvaubt2AX36yLseIiKiZkghCIIQ60Wcz2KxIDk5GWazGUlJSbFeTrPl8Drw7Ppn8dyG50Qd3zt1HLrr7obPm4r0RB20amVYY6+i5cCBA+jRo0eDx7Rp0wa33norrrrqqnpjqCIZ5RUrcs3vJiICEFm22OMB4qy3BxERUTSEE4c2j1QqiXK4/DD+9N2fsKxwmajjr+30ADrqbobPr4TbF8AZqxtJBg06pCUgQatudOxVtOzYsQP9+vVr8Jh+/fph8uTJGD58eMgxVFJGecWDhhqQERE1yuORvj/5oYeA+fNZpk1ERNQABtHN3LcHvsXMJTNRaitt9NiOyR2xaNIi5HfNB1Cb8bS6vfhqWxHUSiW6ZzY89ipaGdGCggKMHTu2wWMmT56MUaNGYfTo0Y2OoQpnlBezvETU7L39NnDPPdLO3b0b6N1b3vUQERG1YAyimxmXz4WXfnwJT6x9QtTxU3pMwWtjX0OnlE71HqvOeJ4sd+CszYOclPpjrxQKBbKT9ThUZkNRpVPWDOk///lP3H777Q0ec8cdd+DKK68MewxVQ6O8ovmaiIiaTCTZ4ooK6bOfiYiIWjkG0c3A8crjmLNiDr7a/5Wo458e/jT+MvQv0KvFdV29cOzVhQxaFU5bXLB7fGKXHNLLL7+Mv/zlLyEf79q1K26++WYMHTo0ojFUTfmaiIiahM8nfX/yK68Af/4zy7SJiIhkwCA6ThUcLsDMb2fiuPl4o8dmmbKwaOIiTLpokqTnMmrV0KtVcHh8SNTX/4Dm9PihU6tg1Eq7Xf76179i/vz5IR8fctUwTJ4wHiNHjpRtDFW0XxMRUZP49ltg8mRp5372GXDDDfKuh4iIiBhExwuP34PX/vcaHv7+YVHHdzZeicFt7kdmQid0TTehZ2qm5OfOTTGga7oJe4rNMOnUdcqfBUFAidmFPrnJyE0RnxW+7bbb8O9//zvk45ePvhbJnS9BVq+BSM9qB1O6CakdM2Wb4xyN10RE1CQiyRabzQAnWxAREUUVg+gYKrIU4f6C+/HJL5+IOv6uyx6A0XMjbE71r92m5emgrVQqMLZ3JorNThSWVe0jNmhVcHr8KDG7kGbUIr9XZqMNuO6++24sXLgw5ON//vOf0fniS3FMnwcHdLK+hmi9JiKiqAsEAJVK2rl6PWC3AzL9ApKIiIgaxyC6ia09thZ3LrkTB88dbPRYnTIZY7Iew9gu1yK/dyZW/lKGPWZzVLpN52UkYsbQTjUzlU9bXNCpVeiTm4z8XqFnKv/mN7/Bxx9/HPSxrI55mDptKqaMG42hQ4dCpVJj4drDcBRH5zXI9ZqIiKJu6VJg4kRp5+7dC/TsKe96iIiISDQG0VHm9Xux4KcFmFswV9TxHU0DcUXqX3Bxes+aLO0vJRYUnrHB7vahQ1pC1LpN52UkostwE4oqnbB7fDBq1chNMdQLaPv06YM9e/YEvUaPQSPRo/8Q5F58OXxJOTCadGh3cSdoNBqcLHc0ecdssa+JiCjqIinTLisD0tPlWwsRERFJxiA6Ck7bTuPBVQ/iXzv/Jer4BwY/gMeuehwf/a8Me0JkabedqMAZqxsXZQbPnkbSbbp6XnRDQWZDM5mvmnwrNNkX4eqRo5GU2rbm64Ig1Mkux6pjdvUoLyKiJiUI0susb7oJWLyYZdpERERxiEG0TDae3Ig7l9yJPWXBM7TnS9Ak4L1J7+GW3rfUBKdisrTHzzlwxupGdpBmWFK7TR8qs9aUO7t8fujVKnRNN2Fs70x0ywzdnOaxxx7DFVdcge6XXoGFG04iJUFTrwv2hdlldswmohZv61ZgwABp5770EvDAA/Kuh4iIiGTHaCUC/9n9H9z6xa2ijr2yw5V465q3cEnmJUEfbyxLm56oQ4JWhWKzE1kXBNpSu00fKrPi/R+Podzu+bXJlwF/Gdcj6LHdunXDzJkzMWzYsDpjqPaXWkRll60uL4w6NZIMahw+Y8Mlucl1OnGzYzYRNVuRlGmfOwekpcm3FiIiIoo6BtESfbLnk0YD6HsH3ounRzyNFH1Ko9drLEvr8gbQPi0BRq1alm7TgYCAFXtOo9zuwTu/C5416XvlGNz12xsxbtxYdOzYUdK6nR4/3L4AvtpejLM2N87a3DhZ7kBJpQu9c5OQnWJgx2wian4iCZx9PunduImIiCjmGERLtO/svnpfUyvVWDRxEaZfOh1KRXj72MTMNb6sQypG98zEyr2Rd5tWqYKv7+rrpqNTr37I7TUILoUe14zp3uB+4sbWXVhmg8XphVqpQE6KATkpBrQ1abGn2ILtJypx1uZBW5OOHbOJKL6dPSu9sdfXXwOTJ8u7HiIiIooZBtESPTT0IaToU/DV/q/wSv4r6J/TP6LriZ1rnJeRiLwMad2mdTodPB5Pva+P//0cdO51GTr3ugwqdVU22RcI4NhZe6NNvhpad3GlCxanF0l6DbpnJtYE2O3TjMhNMWBXkRld2powY2gntEtNYAaaiOJLhw7AyZPSzj16FOjUSdblEBERUXxQCIIgxHoR57NYLEhOTobZbEZSUujGVi3V+Y2+3L6qRlt5GSZJWVpBEOrsO66WmJiIBx97CoWqDujS7SIk6jWwunzw+APQqpRI1Kthc/tQ6fDiz41kohtad9tELY6csaNDWkLQUm+ryxvWcxARRZ3UMu2EBKC8HNDp5F0PERERNYlw4lBmouNMpHONQwXOo0aNwm233YZx48YhIyMDgYCAhWsPY9ORc/AFAqhweOHzB6BWKZGaoIFaqcTgrm1EN/kKtm6r24sFqw8hIUS37WiNtCIiEq2kBMjJkXbuokXAHXfIux4iIiKKewyi44SYWc2hhAqc7777blxzzTUYOXIkDIa6wbBSqUCP7ER8uaMIVpcXbYxaJBk0sLq8OHjaikS9BtMzO4VVYn3hPOaT5Q6OtCKi+DNvHvDUU9LOPXgQ6NZN1uUQERFR88LoJQ40NKs5VAl3qMD52WefxZgxY+qMoQomEBCwv8SK7GQ90o1alFpdKLW44PMLUCsBh8ePDzceQ4c2BnRvYF50Q8Q0S+NIKyJqEpF003a7Aa1WvrUQERFRs8YgOsaCzWp2eHzYU2xGsdmJGUM71QTSfr8fanX9H9k777yDcePGhRxDFUxRpROHz9jQLcMEjz+AcocHRq0aiXo1jFo17B4fDp+x4a01h3HvyDxJXbPFNktjQzEikp3TWbVPWYonnqjKVkcSeBMREVGLFd4cJpLV+bOau2WYkKjXQKVUIFGvQbcME8rtHizdfgIKhQIKhaImgDaZTPjkk09QWVkJQRBw5513hhVAA4Dd44PL54dBo8KRMjv8AQHZyXok6jVQKhUw6tRI0KpwzuZGwS+nEQhI6z+Xl5GIGUM7oXdOMiodXhw7a0elw4s+ucl1fkFARBSx2bOrAl+FIvwAuqgIEISqP089xQCaiIiIQmImOoaqs8HZyfo6pc5upx2PXHtZnWPz8/PxyCOPYOjQodBo6u8vDpdRq4ZercIZqxvlDg9M+rrl1t5fm4xlJ+txqMyGokqn5A7akTZLIyIKKZJg12wGWuEUCCIiIooMg+gYqs4GJ2gN8LiceHjypXUev/qGGcgZOB5P/C4fPbOTZX3u6v3K/ztyFl6/H4n62ltBEATYXD5kJOmRnqjD8XOOiDtoX9h0jIhIEr8fCLKtRZSXXwbmzmWWmYiIiCLCIDqWPC4s/O2AOl+actej6Dd8AhJT29TMUTbpIs88X6h6v/LB01YcOWOHXe2DUaeG1x+AzeWDQatG13QTXN4AO2gTUWytXAnk50s7d+lS4Jpr5F0PERERtWqMjJqYy+WqN24q/08vYuTofGj1tV9viu7VeRmJuGdEHv62ZC8On7HB46sq4c5I0qNrugmpCRoUltnYQZuIml4k2WKHAzDwPYuIiIiig43FmoDdbsecOXOgUChgMBhgMBiwefNm+P1+FJ62YMDwcThm9sHq8sIXCMDq8qKwzNYk3au7ZyXi8Uk9cXnnNGQl69EnNwmXtk+GRqVosjUQEUEQapuChRtAd+4MBAK1jcEYQBMREVEUMYiOEo/Hg2XLlmHWrFno0qULvF4vjh07BkEQ4HA4MHDgQCiVyrjoXt09Mwn3jszD4C5t4Q8Ax8852EGbiKJv+/baoLmBufZBbdlSGzQfOcJ9zkRERNRkFIIgSJtdFCUWiwXJyckwm81IamZdU10uFwoKCrB69Wr4fD5cffXVGDt2LJKTG28KFggIMe9eHQ9rIKIWLpJgt6QEyMqSby1EREREvwonDuWe6Ag5HA5899132LFjB5RKJUaMGIGXX365ZqazWPHQvToe1kBELZDUwHnuXOCll8LPUhMRERFFEYPoCOzbtw+rV6/GyJEjcd1119WZsxzPmHEmoqg6dw5o21bauUuWABMmyLseIiIiIhkxiI5Az5490bNnz1gvIyyHyqxYsec0Dp+xweXzQ69WoWu6CWN7Z3LvMxFJ98ADwCuvSDv33DkgLU3e9RARERFFCYPoVuRQmRXv/3gM5XYPspP1SNAa4PD4sKfYjGKzk03EiCg8kVTf+P0s0yYiIqJmiZ9gWolAQMCKPadRbvegW4YJiXoNVEoFEvUadMswodzuQcEvpxEIxFWfOSKKJzab9DFUn35a201bEBhAExERUbPFTzFxJhAQcLLcgf2lFpwsd8gW1BZVOnH4jA3Zyfp6e7cVCgWyk/U4VGZDUaVTlucjohbinntqg+bEMCtVzpypDZpvvDE66yMiIiJqYiznjiPR3K9s9/jg8vmRoDUEfdygVeG0xQW7xxfR8xBRCyC1TLtjR+DAAUCnk3c9RERERHGEmeg4Ub1feU+xGSkJGnRpa0JKggZ7is14/8djOFRmDXmumOy1UauGXq2CI0SQ7PT4oVOrYNTy9ypErY7fL71M+/PPa7PNx44xgCYiIqIWjxFTHLhwv3J1uXWiXgOTTo3CMhsKfjmNLm1N9UZRic1e56YY0DXdhD3FZph06jol3YIgoMTsQp/cZOSmBM9UE1EL89//AlOnSjt33z6gRw9510NERETUTDCIjgOnKhzYVVSJBI0KVpcPifraIPfC/crt0xJqzgun27ZSqcDY3pkoNjtRWFa1N9qgVcHp8aPE7EKaUYv8XpmcF03UkkVSpn3wIKDVyrseIiIiomaIQXSMHSqz4qP/ncCeU2botUpoVCqkJWjRNcOINGNVWWSw/cpSstd5GYmYMbRTTeb6tMUFnVqFPrnJyO/FOdFELU4kXbBvvRX46KPIxlgRERERtUAMomOoOpN8qsIBvVb1a5k1UGZ1wer24tL2KUgz6oLuVw6n2/b52eu8jER0GW5CUaUTdo8PRq0auSkGZqCJWopNm4DBg6Wde+QI0LmzvOshIiIiamEYRDehQECoCV4TNCp8t7sU5XYPLslNhscn4Iy1qqw6zahFud2Dw2fsSDFogu5XPr/btiAIsLp88PgD0KqUSNSrG+y2rVQq6gTWRNTMRZIttljCH11FRERE1IoxiG4iFzYA8wcEnCx3okeWCUqlEnkZJtjcPpTbPTDp1UjQVQXBu4rMaJeaUG+/cnW37eJKB0rMblQ4PPD5A1CrlEhN0CI7Wcdu20QtmdTA+cMPgd/9jmXaRERERBIxwmoCwRqAFVU4UG5348BpwKjTIM2oxaXtU3CozIYKhwdefwAurx+d2xrx2ys61tuvnJtiQIpBg5X7TkOrViJRr4FGr4bXL6DM6sKpCgfyL85kt22ilsLhAIxGaeeuXg2MGCHveoiIiIhaKQbRURaqAVhKghbJBg1sLh8On7EhNSEVaUYtLu+UCqvLhwqHB06PHzOGdkbHNiE+OFcnkgQBgPDrF36d1/rrV4ioGbvhBuCLL6Sd63AABv4SjYiIiEhuDKKjLFQDsES9Gm2MOhRVOlBuc8Pq8iHJoIFCoUCiXo1Siwt926egfWrwvctFlU5UOry4vFMqSs1ulDs8sLt9UCmVyEw2ICtJh0qHt15jMSKKc1LLrDt0AI4dY5k2ERERUZQxiI6y8xuAnU+hUKBrhhFmlwfnbB5UODxI0Imf21x93S5tTWiXmlCvsZhfEHDsrD1oYzEiiiN2O2AySTt3716gZ09510NEREREDWIQHWXVDcAcHh8S9Zo6j6UZdbgoMxH7BSucHj+OnbWLntt84XWTDHWv7XT72FiMKF6tXw8MGybt3HPngLQ0eddDRERERKLJHmHNmzcPTz31VJ2vZWZmorS0VO6nahZyUwzomm7CnmLzr3OgazPLgiDA6Q1gQp8cTOybDafXL3puc2PXDTYWi4hiSGqZ9fTpwPvvs0ybiIiIKE5EJU3Zq1cvrFq1qubvKpUqGk/TLCiVCoztnYlisxOFZVV7ow3aumXbY3tnhm4eFsF1GyoHJ6IoCwQAqe99n31W1VSMiIiIiOJOVIJotVqNrKysaFy6WcrLSMSMoZ1q5kSftrhClm0HAgKKKp2we3yNZqXDuS4RNYEtW4DLL5d2blkZkJ4u73qIiIiISHZRCaILCwuRk5MDnU6HQYMG4bnnnkOXLl2CHut2u+F2u2v+brFYorGkmMvLSESX4aYGA+RDZdaagNjl80OvVqFruglje4cOiMVcl4iiSGqZdUYGUFwsPVtNRERERDGhEARB1nHCy5cvh8PhQPfu3XH69Gk888wz2L9/P3755Re0adOm3vHB9lADgNlsRlJSkpxLi2uHyqx4/8djKLd7kJ2sR4JWDYfHV1OaPWNoJ2aWieKBIABKpbRzP/8cuP56eddDRERERBGzWCxITk4WFYfKHkRfyG63o2vXrnjwwQcxd+7ceo8Hy0S3b9++VQXRgYCAhWsPY0+xGd0yTPWahBWW2dAnNxmzhnVlhpkoFkpLgexsaeeePQsE+QUiEREREcWPcILoqM8/MhqN6NOnDwoLC4M+rtPpoNPpor2MuFZU6cThM1XNwRQXlIYqFApkJ+txqMyGokon2qclxGiVRK1M//7Atm3SznW7Aa1W3vUQERERUVyQWJMontvtxr59+5AtNYvTCtg9Prh8fiSEmOls0Krg9vlh9/iaeGVErYxCUfsnnAB6xYqqbtyCUPWHATQRERFRiyV7EP3AAw9g3bp1OHr0KDZv3owbb7wRFosF06dPl/upWgyjVg29WgVHiCDZ6fFDp1bBGCLIJiKJPJ66gXM4du6sDZrz8znHmYiIiKiVkD2IPnXqFG655RZcdNFFuP7666HVarFp0yZ07NhR7qdqMXJTDOiabkKJ2YULt6gLgoASswt5GSbkphhitEKiFmTRotqgOZytJElJgM9XGzhfckn01khEREREcUv21ObixYvlvmSLp1QqMLZ3JorNThSWVe2NNmhVcHr8Nd2583tlsqkYkVRSs8Q33QR88gmzzERERERUg/XBcSIvIxEzhnaqmRN92uKCTq1Cn9xk5PcKPSeaiIIIBKTPXz51CsjNlXc9RERERNRiMIiOI3kZiegy3ISiSifsHh+MWjVyUwzMQBOJsX07cNll0s612QCjUd71EBEREVGLxCA6ziiVCo6xIhJLapn1008Djz8u71qIiIiIqFVgEE1EzYvUwLmgABgzRt61EBEREVGrwyCaiOLbgQNAjx7SzmWZNhERERHJTPYRV0REERs4sHYMVTgB9ODBgN9fO4aKATQRERERyYyZaCKKD1LLtLdvBy69VNalEBERERGFwiCaiGLDagWSkqSda7cDCWzAR0RERERNj+XcRNR0Zs+uLdMOJ4BOSwN8vtoybQbQRERERBQjzEQTUXSxmzYRERERtSAMoolIXoEAoFJJO7ekBMjKknc9REREREQyYjk3EUVu/fraMu1wAuhLL60KuqvLtBlAExEREVGcYyaaiKSRWqb9xhvAn/4k71qIiIiIiJoIg2giEk9q4Hz2LNCmjbxrISIiIiKKAQbRRBSazQYkJko71+UCdDp510NEREREFGPcE01EdT31VO3+5nAC6P/8p3ZvsyAwgCYiIiKiFomZaCKSXqa9YwfQt6+sSyEiIiIiimcMoolao0jGULFMm4iIiIhaMZZzE7UW+/ZJG0OVn193DBUDaCIiIiJqxZiJJmrJBg0Cfvop/POOHAE6d5Z/PUREREREzRyD6CgKBAQUVTph9/hg1KqRm2KAUilx7ymRGIIAKCUWmFgs0jtxExERERG1Egyio+RQmRUr9pzG4TM2uHx+6NUqdE03YWzvTORlMFAhGR09CnTpEv55kycDX30lvakYEREREVErxD3RUXCozIr3fzyGPcVmpCRo0KWtCSkJGuwpNuP9H4/hUJk11kuk5m7y5Nr9zeEE0N9/X7u3+euvGUATEREREYWJmWiZBQICVuw5jXK7B90yTFD8GqQk6jUw6dQoLLOh4JfT6NLWxNJuCo/UgNftBrRaeddCRERERNRKMRMts6JKJw6fsSE7WV8TQFdTKBTITtbjUJkNRZXOGK2Qmg23uzbbHG4AXZ1tFgQG0EREREREMmIQLTO7xweXz48EbfAkv0Grgtvnh93ja+KVUbOwYEFt0KzXiz/vm2/qBs5ERERERBQVLOeWmVGrhl6tgsPjQ6JeU+9xp8cPnVoFY4ggm1ohqWXaZjOQlCTvWoiIiIiIqEHMRMssN8WArukmlJhdEC7ICAqCgBKzC3kZJuSmGGK0Qoo5QZBepu311mabGUATERERETU5BtEyUyoVGNs7E2lGLQrLbLC6vPAFArC6vCgssyHNqEV+r0w2FWttjh6tDZrDmeNcUFC3TFvNCgYiIiIioljiJ/IoyMtIxIyhnWrmRJ+2uKBTq9AnNxn5vTgnutXIywMOHw7/vFOngNxc+ddDREREREQRYxAdJXkZiegy3ISiSifsHh+MWjVyUwzMQLd0Uvc3ezyApv4eeiIiIiIiii8s544ipVKB9mkJ6JGVhPZpCQygWyKPR9r+5ltuAQKB2jJtBtBERERERM0Cg2iicL3+em3QrNOJP+/Mmdqg+eOPpWetiYiIiIgoZljOTSSG1IDX5Qov0CYiIiIiorjGTDRRMFLHUN1/f90ybQbQREREREQtCjPRRNUOHQK6dQv/vM2bgYED5V8PERERERHFHQbR1LqNHAmsWRP+eT4foFLJvx4iIiIiIoprDKKp9ZG6vzkQYDMwIiIiIqJWjnuiqeVzuaTtb/7xx9q9zdV7pImIiIiIqFVjEE0t0z/+URs0GwzizzOba4PmIUOitz4iIiIiImqWWM5NLYeUTHFiImCxyL8WIiIiIiJqkZiJpuZL6hiqlStrs80MoImIiIiIKAzMRFPz8tNPwKBB4Z9XWQkkJ8u+HCIiIiIial0YRFP8k9rQi2OoiIiIiIhIZiznpvgkpUz7mWfqdtNmAE1ERERERDJjJprig8MBGI3hn2ezSTuPiIiIiIhIAmaiKXbuuqs22xxOIOz11mabGUATEREREVETYiaampaU/c133QW8/bb8ayEiIiIiIgoTg2iKLkEAlBIKHvbtA3r0kH89REREREREEWAQLVEgIKCo0gm7xwejVo3cFAOUSoldpFuaXbuAvn3DPy8QkN6Jm4iIiIiIqAkwiJbgUJkVK/acxuEzNrh8fujVKnRNN2Fs70zkZSTGenmxodcDbnf45zFwJiIiIiKiZoSNxcJ0qMyK9388hj3FZqQkaNClrQkpCRrsKTbj/R+P4VCZNdZLbDrnj6ESG0Bv2lR3DBUDaCIiIiIiakaYiQ5DICBgxZ7TKLd70C3DBMWvAWCiXgOTTo3CMhsKfjmNLm1NLbO02+UCDIbwz3M4pJ1HREREREQUZ5iJDkNRpROHz9iQnayvCaCrKRQKZCfrcajMhqJKZ4xWGAULFtRmm8MJhM/PNjOAJiIiIiKiFoJBdBjsHh9cPj8StMET+AatCm6fH3aPr4lXJrPzy7TvvVfcOW+9VTdwJiIiIiIiaoFYzh0Go1YNvVoFh8eHRL2m3uNOjx86tQrGEEF23JI6hspiARJbaSM1IiIiIiJqlZiJDkNuigFd000oMbsgXJBtFQQBJWYX8jJMyE1pBuXLx47VZpvDCaADgdpsMwNoIiIiIiJqZRhEh0GpVGBs70ykGbUoLLPB6vLCFwjA6vKisMyGNKMW+b0y47ep2Asv1AbOnTuLO+eNN9hNm4iIiIiI6FfNrO449vIyEjFjaKeaOdGnLS7o1Cr0yU1Gfq84nBMtJehlN20iIiIiIqKgGERLkJeRiC7DTSiqdMLu8cGoVSM3xRAfGWivF9Bqwz/P75e2L5qIiIiIiKgVYdQkkVKpQPu0BPTISkL7tITYBtCbNtWWaYsNoGfMqFumzQCaiIiIiIioUYycmquHHqoNnAcPFnfOrl21QfM//xnd9REREREREbVALOduTqTsbw4E2AyMiIiIiIhIJsxEx7OzZ2uzzeEEwuymTUREREREFBUMouPNZ5/VBs3p6eLOWbWqbuBMREREREREUcFy7njwxRfADTeEd47HA2g00VkPERERERERBcVMdCwIAjB3bm3GWUwA3b173WwzA2giIiIiIqImxyC6qZjNwBVXVAXNSiXw2muNn/O3v9UGzQcORH+NRERERERE1CCWc0dTUREwZQqwZYv4cyorgeTkaK2IiIiIiIiIIsBMtNx++AHo0aMq49yuXeMB9FtvVY2hqs44M4AmIiIiIiKKW8xERyoQALZtA775pqr8Woxdu4A+faK7LiIiIiIiIpIdg+hI+HxVDb+OHm34uJtvBhYsED+yioiIiIiIiOISy7kjoVZXBdEXMhiAjz6qLdP+5BMG0ERERERERC0AM9GRuummqnFTkycDEyYAOTmxXhERERERERFFiUIQBCHWizifxWJBcnIyzGYzkpKSYr0cIiIiIiIiauHCiUNZzk1EREREREQkEoNoIiIiIiIiIpEYRBMRERERERGJxCCaiIiIiIiISKSoBdFvv/02OnfuDL1ej/79++OHH36I1lMRERERERERNYmoBNGffPIJ5syZg0cffRTbt2/HVVddhfHjx+PEiRPReDoiIiIiIiKiJhGVEVeDBg3CZZddhoULF9Z8rWfPnpgyZQrmz5/f4LkccUVERERERERNKaYjrjweD7Zu3Yr8/Pw6X8/Pz8fGjRvrHe92u2GxWOr8ISIiIiIiIopHsgfRZ8+ehd/vR2ZmZp2vZ2ZmorS0tN7x8+fPR3Jycs2f9u3by70kIiIiIiIiIllErbGYQqGo83dBEOp9DQAeeeQRmM3mmj8nT56M1pKIiIiIiIiIIqKW+4Jt27aFSqWql3UuKyurl50GAJ1OB51OJ/cyiIiIiIiIiGQneyZaq9Wif//+WLlyZZ2vr1y5EkOGDJH76YiIiIiIiIiajOyZaACYO3cufve732HAgAEYPHgwFi1ahBMnTmDWrFnReDoiIiIiIiKiJhGVIHrq1Kk4d+4cnn76aZSUlKB3795YtmwZOnbsGI2nIyIiIiIiImoSUZkTHQnOiSYiIiIiIqKmFNM50UREREREREQtFYNoIiIiIiIiIpEYRBMRERERERGJxCCaiIiIiIiISCQG0UREREREREQiMYgmIiIiIiIiEikqc6IjUT1xy2KxxHglRERERERE1BpUx59iJkDHXRBttVoBAO3bt4/xSoiIiIiIiKg1sVqtSE5ObvAYhSAm1G5CgUAAxcXFSExMhEKhiPVygrJYLGjfvj1OnjzZ6CBuovPx3iGpeO+QVLx3SCreOyQV7x2SItb3jSAIsFqtyMnJgVLZ8K7nuMtEK5VKtGvXLtbLECUpKYlvDCQJ7x2SivcOScV7h6TivUNS8d4hKWJ53zSWga7GxmJEREREREREIjGIJiIiIiIiIhKJQbQEOp0OTz75JHQ6XayXQs0M7x2SivcOScV7h6TivUNS8d4hKZrTfRN3jcWIiIiIiIiI4hUz0UREREREREQiMYgmIiIiIiIiEolBNBEREREREZFIDKKJiIiIiIiIRGIQTURERERERCQSg+gwvf322+jcuTP0ej369++PH374IdZLojgzb948KBSKOn+ysrJqHhcEAfPmzUNOTg4MBgOGDx+OX375JYYrplhZv349Jk2ahJycHCgUCnz11Vd1Hhdzr7jdbtx7771o27YtjEYjJk+ejFOnTjXhq6BYaOze+f3vf1/vfeiKK66ocwzvndZn/vz5uPzyy5GYmIiMjAxMmTIFBw4cqHMM33coGDH3Dt93KJiFCxfikksuQVJSEpKSkjB48GAsX7685vHm+p7DIDoMn3zyCebMmYNHH30U27dvx1VXXYXx48fjxIkTsV4axZlevXqhpKSk5s/u3btrHnvxxRfx6quvYsGCBfj555+RlZWFMWPGwGq1xnDFFAt2ux19+/bFggULgj4u5l6ZM2cOvvzySyxevBgbNmyAzWbDxIkT4ff7m+plUAw0du8AwLhx4+q8Dy1btqzO47x3Wp9169bhnnvuwaZNm7By5Ur4fD7k5+fDbrfXHMP3HQpGzL0D8H2H6mvXrh2ef/55bNmyBVu2bMHIkSNx7bXX1gTKzfY9RyDRBg4cKMyaNavO13r06CE8/PDDMVoRxaMnn3xS6Nu3b9DHAoGAkJWVJTz//PM1X3O5XEJycrLwzjvvNNEKKR4BEL788suav4u5VyorKwWNRiMsXry45piioiJBqVQK3333XZOtnWLrwntHEARh+vTpwrXXXhvyHN47JAiCUFZWJgAQ1q1bJwgC33dIvAvvHUHg+w6Jl5qaKvz9739v1u85zESL5PF4sHXrVuTn59f5en5+PjZu3BijVVG8KiwsRE5ODjp37oxp06bhyJEjAICjR4+itLS0zn2k0+kwbNgw3kdUh5h7ZevWrfB6vXWOycnJQe/evXk/EdauXYuMjAx0794dd9xxB8rKymoe471DAGA2mwEAaWlpAPi+Q+JdeO9U4/sONcTv92Px4sWw2+0YPHhws37PYRAt0tmzZ+H3+5GZmVnn65mZmSgtLY3RqigeDRo0CP/617+wYsUKvPfeeygtLcWQIUNw7ty5mnuF9xE1Rsy9UlpaCq1Wi9TU1JDHUOs0fvx4/L//9/+wevVqvPLKK/j5558xcuRIuN1uALx3qGof4ty5c3HllVeid+/eAPi+Q+IEu3cAvu9QaLt374bJZIJOp8OsWbPw5Zdf4uKLL27W7znqmD1zM6VQKOr8XRCEel+j1m38+PE1/92nTx8MHjwYXbt2xYcffljTYIP3EYkl5V7h/URTp06t+e/evXtjwIAB6NixI5YuXYrrr78+5Hm8d1qP2bNnY9euXdiwYUO9x/i+Qw0Jde/wfYdCueiii7Bjxw5UVlbi888/x/Tp07Fu3bqax5vjew4z0SK1bdsWKpWq3m88ysrK6v32hOh8RqMRffr0QWFhYU2Xbt5H1Bgx90pWVhY8Hg8qKipCHkMEANnZ2ejYsSMKCwsB8N5p7e6991588803WLNmDdq1a1fzdb7vUGNC3TvB8H2Hqmm1WuTl5WHAgAGYP38++vbtizfeeKNZv+cwiBZJq9Wif//+WLlyZZ2vr1y5EkOGDInRqqg5cLvd2LdvH7Kzs9G5c2dkZWXVuY88Hg/WrVvH+4jqEHOv9O/fHxqNps4xJSUl2LNnD+8nquPcuXM4efIksrOzAfDeaa0EQcDs2bPxxRdfYPXq1ejcuXOdx/m+Q6E0du8Ew/cdCkUQBLjd7ub9nhODZmbN1uLFiwWNRiP84x//EPbu3SvMmTNHMBqNwrFjx2K9NIoj999/v7B27VrhyJEjwqZNm4SJEycKiYmJNffJ888/LyQnJwtffPGFsHv3buGWW24RsrOzBYvFEuOVU1OzWq3C9u3bhe3btwsAhFdffVXYvn27cPz4cUEQxN0rs2bNEtq1ayesWrVK2LZtmzBy5Eihb9++gs/ni9XLoibQ0L1jtVqF+++/X9i4caNw9OhRYc2aNcLgwYOF3Nxc3jut3F133SUkJycLa9euFUpKSmr+OByOmmP4vkPBNHbv8H2HQnnkkUeE9evXC0ePHhV27dol/PWvfxWUSqVQUFAgCELzfc9hEB2mt956S+jYsaOg1WqFyy67rE5rfyJBEISpU6cK2dnZgkajEXJycoTrr79e+OWXX2oeDwQCwpNPPilkZWUJOp1OuPrqq4Xdu3fHcMUUK2vWrBEA1Pszffp0QRDE3StOp1OYPXu2kJaWJhgMBmHixInCiRMnYvBqqCk1dO84HA4hPz9fSE9PFzQajdChQwdh+vTp9e4L3jutT7B7BoDw/vvv1xzD9x0KprF7h+87FMof/vCHmtgpPT1dGDVqVE0ALQjN9z1HIQiC0HR5byIiIiIiIqLmi3uiiYiIiIiIiERiEE1EREREREQkEoNoIiIiIiIiIpEYRBMRERERERGJxCCaiIiIiIiISCQG0UREREREREQiMYgmIiIiIiIiEolBNBEREREREZFIDKKJiIiIiIiIRGIQTURERERERCQSg2giIiIiIiIikf4/BK1Txdnf2cAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 7))\n",
    "plt.plot(advertising[\"TV\"], advertising[\"sales\"], 'o', alpha=0.5)\n",
    "plt.plot(advertising[\"TV\"], fittedvalues, 'g-', lw=2, label=\"Fitted model\")\n",
    "plt.plot(advertising[\"TV\"], predict_ci_low, 'r--', lw=2, label=\"Pred Interval\")\n",
    "plt.plot(advertising[\"TV\"], predict_ci_upp, 'r--', lw=2)\n",
    "plt.plot(advertising[\"TV\"], predict_mean_ci_low, 'k-', lw=0.3, label=\"Conf. Interval (mean)\")\n",
    "plt.plot(advertising[\"TV\"], predict_mean_ci_upp, 'k-', lw=0.3)\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Multiple Linear Regression\n",
    "\n",
    "* How can we leverage other information to predict sales?\n",
    "  * Naive solution: Build independent regresison and combine results\n",
    "  \n",
    "* Problems with the naive solution\n",
    "  * Not completely clear how to combine the data\n",
    "    * Min, mean, or median, etc.? Why?\n",
    "    \n",
    "  * Each feature ignores the effect of the other features\n",
    "    * Does not account for interactions\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    9.3116</td> <td>    0.563</td> <td>   16.542</td> <td> 0.000</td> <td>    8.202</td> <td>   10.422</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>radio</th>     <td>    0.2025</td> <td>    0.020</td> <td>    9.921</td> <td> 0.000</td> <td>    0.162</td> <td>    0.243</td>\n",
       "</tr>\n",
       "</table>"
      ],
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       "<class 'statsmodels.iolib.table.SimpleTable'>"
      ]
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     "execution_count": 29,
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   ],
   "source": [
    "est = smf.ols('sales ~ radio', advertising).fit()\n",
    "est.summary().tables[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
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   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>   12.3514</td> <td>    0.621</td> <td>   19.876</td> <td> 0.000</td> <td>   11.126</td> <td>   13.577</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>newspaper</th> <td>    0.0547</td> <td>    0.017</td> <td>    3.300</td> <td> 0.001</td> <td>    0.022</td> <td>    0.087</td>\n",
       "</tr>\n",
       "</table>"
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       "<class 'statsmodels.iolib.table.SimpleTable'>"
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     "execution_count": 30,
     "metadata": {},
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   "source": [
    "est = smf.ols('sales ~ newspaper', advertising).fit()\n",
    "est.summary().tables[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Multiple Linear Regression \n",
    "\n",
    "* We re-write our linear regression equation to account for all variables\n",
    "\n",
    "$$\n",
    "y = \\beta_0 + \\beta_1 x_1 + \\beta_2 x_2 + \\cdots + \\beta_p x_p + \\epsilon\n",
    "$$\n",
    "\n",
    "$\\hspace{0.6in}$where:\n",
    "\n",
    "$\\hspace{0.6in}$ * $p$ is the number of variables in the model\n",
    "  \n",
    "$\\hspace{0.6in}$ * $\\beta_i$ is the mean effect on $y$ for a unit increase in the predictor $x_i$, holding all \n",
    "$\\hspace{0.8in}$the other values constant\n",
    "  \n",
    "\n",
    "* We can use statsmodels to compute the parameters of the new model:\n",
    "\n",
    "$$\n",
    "sales = \\beta_0 + \\beta_1 \\times \\text{TV\\_budget} + \\beta_2 \\times \\text{radio\\_budget} + \\beta_3 \\times \\text{newspaper\\_budget} + \\epsilon\n",
    "$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Estimating the Regression Coefficients\n",
    "\n",
    "<img src=\"https://www.dropbox.com/scl/fi/cornqx9fo5doodbjl3nbk/plane.png?rlkey=t2xytc7f0xhcqzl07z60bcuvu&dl=1\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TV</th>\n",
       "      <th>radio</th>\n",
       "      <th>newspaper</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>TV</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.054809</td>\n",
       "      <td>0.056648</td>\n",
       "      <td>0.782224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>radio</th>\n",
       "      <td>0.054809</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.354104</td>\n",
       "      <td>0.576223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>newspaper</th>\n",
       "      <td>0.056648</td>\n",
       "      <td>0.354104</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.228299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sales</th>\n",
       "      <td>0.782224</td>\n",
       "      <td>0.576223</td>\n",
       "      <td>0.228299</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 TV     radio  newspaper     sales\n",
       "TV         1.000000  0.054809   0.056648  0.782224\n",
       "radio      0.054809  1.000000   0.354104  0.576223\n",
       "newspaper  0.056648  0.354104   1.000000  0.228299\n",
       "sales      0.782224  0.576223   0.228299  1.000000"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "advertising.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>          <td>sales</td>      <th>  R-squared:         </th> <td>   0.897</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.896</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   570.3</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Mon, 27 Mar 2023</td> <th>  Prob (F-statistic):</th> <td>1.58e-96</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>19:12:20</td>     <th>  Log-Likelihood:    </th> <td> -386.18</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>   200</td>      <th>  AIC:               </th> <td>   780.4</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>   196</td>      <th>  BIC:               </th> <td>   793.6</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     3</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    2.9389</td> <td>    0.312</td> <td>    9.422</td> <td> 0.000</td> <td>    2.324</td> <td>    3.554</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TV</th>        <td>    0.0458</td> <td>    0.001</td> <td>   32.809</td> <td> 0.000</td> <td>    0.043</td> <td>    0.049</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>radio</th>     <td>    0.1885</td> <td>    0.009</td> <td>   21.893</td> <td> 0.000</td> <td>    0.172</td> <td>    0.206</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>newspaper</th> <td>   -0.0010</td> <td>    0.006</td> <td>   -0.177</td> <td> 0.860</td> <td>   -0.013</td> <td>    0.011</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>60.414</td> <th>  Durbin-Watson:     </th> <td>   2.084</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.000</td> <th>  Jarque-Bera (JB):  </th> <td> 151.241</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td>-1.327</td> <th>  Prob(JB):          </th> <td>1.44e-33</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 6.332</td> <th>  Cond. No.          </th> <td>    454.</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                  sales   R-squared:                       0.897\n",
       "Model:                            OLS   Adj. R-squared:                  0.896\n",
       "Method:                 Least Squares   F-statistic:                     570.3\n",
       "Date:                Mon, 27 Mar 2023   Prob (F-statistic):           1.58e-96\n",
       "Time:                        19:12:20   Log-Likelihood:                -386.18\n",
       "No. Observations:                 200   AIC:                             780.4\n",
       "Df Residuals:                     196   BIC:                             793.6\n",
       "Df Model:                           3                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept      2.9389      0.312      9.422      0.000       2.324       3.554\n",
       "TV             0.0458      0.001     32.809      0.000       0.043       0.049\n",
       "radio          0.1885      0.009     21.893      0.000       0.172       0.206\n",
       "newspaper     -0.0010      0.006     -0.177      0.860      -0.013       0.011\n",
       "==============================================================================\n",
       "Omnibus:                       60.414   Durbin-Watson:                   2.084\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              151.241\n",
       "Skew:                          -1.327   Prob(JB):                     1.44e-33\n",
       "Kurtosis:                       6.332   Cond. No.                         454.\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "est = smf.ols('sales ~ TV + radio + newspaper', advertising).fit()\n",
    "est.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
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   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    2.9389</td> <td>    0.312</td> <td>    9.422</td> <td> 0.000</td> <td>    2.324</td> <td>    3.554</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>TV</th>        <td>    0.0458</td> <td>    0.001</td> <td>   32.809</td> <td> 0.000</td> <td>    0.043</td> <td>    0.049</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>radio</th>     <td>    0.1885</td> <td>    0.009</td> <td>   21.893</td> <td> 0.000</td> <td>    0.172</td> <td>    0.206</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>newspaper</th> <td>   -0.0010</td> <td>    0.006</td> <td>   -0.177</td> <td> 0.860</td> <td>   -0.013</td> <td>    0.011</td>\n",
       "</tr>\n",
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     "execution_count": 33,
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   "source": [
    "est = smf.ols('sales ~ TV + radio + newspaper', advertising).fit()\n",
    "est.summary().tables[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Model Interpretation\n",
    "\n",
    "<center><img src=\"https://www.dropbox.com/s/btz9dqkzdxkz5qy/results_table.png?dl=1\" width=400></center>\n",
    "\n",
    "* For each additional $1K in TV advertising, we expect, on average, an increase in sales of 45.8 units\n",
    "\n",
    "* For each additional $1K in radio advertising, we expect, on average, an increase in sales of 188.5 units\n",
    "\n",
    "* The newspaper spending is not significant and does not contribute to the model\n",
    "  * Why is it different from when tested independently?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Interaction\n",
    "\n",
    "* Simple linear regression predicts an effect of 0.0547 (54.7 units) for newspaper\n",
    "* Multiple linear regression predicts an effect of ~0\n",
    "\n",
    "* Recall that the  correlation between radio and newspaper is ~0.35\n",
    "    * Positive correlation indicates that in some cases, spending on radio advertising is accompanied by spending on newspaper advertising\n",
    "\n",
    "* What is happening?\n",
    "* radio advertising leads to increased sales\n",
    "\n",
    "* radio and newspaper are correlated\n",
    "  * radio advertising is accompanied by newspaper advertising\n",
    "\n",
    "* Part of the effect of newspaper advertising is actually accounted for by radio advertising\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Some Important Concepts to Explore\n",
    "\n",
    "* In the presence of dozens of predictors, the situation above becomes intractable manually\n",
    "  * Which parameters are linked with which other parameters?\n",
    "  * While the $R^2$ will increase as the number of predictors increases, this is not indicative that the model is getting better\n",
    "    * Often referred to as overfitting\n",
    "    \n",
    "* Identifying the best subset among many variables to include in a model is challenging\n",
    "  * This is discussed in depth in chapters 3 and of (Introduction to Statistical Learning -- excellent book if you'd like to delve deeper into this)\n",
    "\n",
    "* Some advanced models will automatically \"shrink\" the contribution of a feature to a model\n",
    "  * E.g.: ridge regression or lasso regression, shrink the contributions of \"unnecessary\" features.\n"
   ]
  }
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