day15_reading_journal.ipynb

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    "# Day 15 Reading Journal\n",
    "\n",
    "This journal includes several required exercises, but it is meant to encourage active reading more generally.  You should use the journal to take detailed notes, catalog questions, and explore the content from Think Python deeply.\n",
    "\n",
    "Reading: Think Python Appendix B (through B.2)\n",
    "\n",
    "**Due: Thursday, March 23 at 12 noon**\n"
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    "## [Appendix B](http://www.greenteapress.com/thinkpython2/html/thinkpython2022.html)\n",
    "\n",
    "You only need to read as far as section B.2 (inclusive), but feel free to go further and try more exercises if you are interested."
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    "1. Analysis of algorithms: study algorith performance\n",
    "2. Machine Model: number of steps to complete on a specific computer\n",
    "3. Analyze worst case scenario to optimize\n",
    "4. Run time is related to the power of the exponent of N\n",
    "5. The higher the power the longer the runtime\n",
    "6. Having high coefficients and high exponents will be efficient at the lower end, but not with higher values\n",
    "7. Big Oh Notation O(n) is n^n\n",
    "8. If body of loop is O(n^a) whole loop is O(n^a+1)"
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    "### Exercise 1  \n",
    "\n",
    "Read the [Wikipedia page on Big-Oh notation](http://en.wikipedia.org/wiki/Big_O_notation) and answer the following questions:\n",
    "\n",
    " 1. What is the order of growth of n<sup>3</sup> + n<sup>2</sup>? What about 1000000 n<sup>3</sup> + n<sup>2</sup>? What about n<sup>3</sup> + 1000000 n<sup>2</sup>?\n",
    " 2. What is the order of growth of (n<sup>2</sup> + n) * (n + 1)? Before you start multiplying, remember that you only need the leading term.\n",
    " 3. If f is in O(g), for some unspecified function g, what can we say about af+b?\n",
    " 4. If f<sub>1</sub> and f<sub>2</sub> are in O(g), what can we say about f<sub>1</sub> + f<sub>2</sub>?\n",
    " 5. If f<sub>1</sub> is in O(g) and f<sub>2</sub> is in O(h), what can we say about f<sub>1</sub> + f<sub>2</sub>?\n",
    " 6. If f<sub>1</sub> is in O(g) and f<sub>2</sub> is O(h), what can we say about f<sub>1</sub> * f<sub>2</sub>? "
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    "solution": "Exercise B.1"
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    "  1. They are all n^3\n",
    "  2. n^3\n",
    "  3. It is still O(g). Multiplying by a constant does not change it.\n",
    "  4. It will be of the same order. Adding order does not make it any bigger\n",
    "  5. The combined function will be O(g) if g > h and O(h) if h > g\n",
    "  6. The combined function will be in O(g+h)"
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    "problem": "Feedback"
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   "source": [
    "## Reading Journal feedback\n",
    "\n",
    "[Please complete this short survey](https://docs.google.com/forms/d/e/1FAIpQLScQekhUrf6YYjpfQiAAbavLIA-IJklv_PX1BWbGgxj7JPolmw/viewform?c=0&w=1)\n",
    "\n",
    "If you have any comments on this Reading Journal, feel free to leave them in the survey linked above. This could include suggestions to improve the exercises, topics you'd like to see covered in class next time, or other feedback.\n",
    "\n",
    "If you have Python questions or run into problems while completing the reading, you should post them to Piazza instead so you can get a quick response before your journal is submitted."
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