Preliminary (#76)

* Make the same update

* Update readme

07-inference-num.Rmd

@@ -49,7 +49,7 @@ We'll first learn about this new distribution, then we'll use it to construct co
 Consider a situation where you want to know whether you should buy a franchise of the used car store Awesome Autos.
 As part of your planning, you'd like to know for how much an average car from Awesome Autos sells.
 In order to go through the example more clearly, let's say that you are only able to randomly sample five cars from Awesome Auto.
-If this were a real example, you would surely be able to take a much larger sample size, possibly even being able to measure the entire population!
+(If this were a real example, you would surely be able to take a much larger sample size, possibly even being able to measure the entire population!)
 
 #### Observed data {.unnumbered}
 

README.md

@@ -1,9 +1,5 @@
-[![Netlify Status](https://api.netlify.com/api/v1/badges/2afbdb92-43e5-415b-b3dd-61a4d9168b0f/deploy-status)](https://app.netlify.com/sites/openintro-ims/deploys)
-
 # Introduction to Modern Statistics
 
-**THIS IS A WORK IN PROGRESS!!!**
-
 ## Where did Introduction to Statistics with Randomization and Simulation go?
 
 As we're working on the 2nd edition of this book, we realized that we weren't too enamoured by the name, and decided to rename the book to "Introduction to Modern Statistics" to better reflect the content covered in the book, which features simulation-based inference but also many non-inference topics!
@@ -14,110 +10,129 @@ If you're looking for the source files for the 1st edition of OpenIntro - Introd
 
 Some restructuring, some reordering, and some new content with better treatment of randomization and simulation throughout the book.
 
-Each section comes with exercises as well as chapter level exercises in the last (review) section of each chapter. The review section also includes interactive R tutorials and labs.
+Each section comes with exercises as well as chapter level exercises in the last (review) section of each chapter.
+The review section also includes interactive R tutorials and labs.
+
+## Preliminary edition
 
-Tentative outline:
+Preliminary edition of Introduction to Modern Statistics is now complete and can be found at <https://openintro-ims.netlify.app>.
 
 ### [Chp 1. Getting started with data](https://openintro-ims.netlify.app/getting-started-with-data.html)
 
 *Complete*
 
-- Case study
-- Data basics
-- Sampling principles and strategies
-- Experiments
-- Chapter review
+-   Case study
+-   Data basics
+-   Sampling principles and strategies
+-   Experiments
+-   Chapter review
 
 ### [Chp 2. Summarizing and visualizing data](https://openintro-ims.netlify.app/summarizing-visualizing-data.html)
 
-*Exercises to be added to effective data viz section*
+*Complete*
 
-- Exploring numerical data
-- Exploring categorical data
-- Effective data visualization
-- Case study
-- Chapter review
+-   Exploring numerical data
+-   Exploring categorical data
+-   Effective data visualization
+-   Case study
+-   Chapter review
 
 ### [Chp 3. Introduction to linear models](https://openintro-ims.netlify.app/intro-linear-models.html)
 
-*Complete, exercises need to be formatted*
+*Complete*
 
-- Fitting a line, residuals, and correlation
-- Least squares regression
-- Outliers in linear regression
+-   Fitting a line, residuals, and correlation
+-   Least squares regression
+-   Outliers in linear regression
 
 ### [Chp 4. Multivariable and logistic models](https://openintro-ims.netlify.app/multi-logistic-models.html)
 
-*In progress*
+*Complete*
 
-- Regression with multiple predictors
-- Model selection
-- Model diagnostics
-- Case study: Mario Kart
-- Logistic regression
+-   Regression with multiple predictors
+-   Model selection
+-   Logistic regression
 
 ### [Chp 5. Introduction to statistical inference](https://openintro-ims.netlify.app/intro-stat-inference.html)
 
-*Complete, exercises need to be formatted*
+*Complete, exercises need to be added*
 
-- Randomization tests
-  - Case study: Gender discrimination
-  - Case study: Opportunity cost
-- Bootstrap confidence intervals
-- Mathematical models
+-   Randomization tests
+-   Bootstrap confidence intervals
+-   Mathematical models
 
 ### [Chp 6. Inference for categorical responses](https://openintro-ims.netlify.app/inference-cat.html)
 
-*Complete, exercises need to be formatted*
-
-- One proportion
-  - Bootstrap test
-  - Bootstrap confidence interval
-  - Mathematical model
-- Difference of two proportions
-  - Randomization test
-  - Bootstrap confidence interval
-  - Mathematical model
-- Independence in two way tables
-  - Randomization test
-  - Bootstrap confidence interval
-  - Mathematical model
-
+*Complete, exercises need to be added*
+
+-   One proportion
+
+    -   Bootstrap test
+    -   Bootstrap confidence interval
+    -   Mathematical model
+
+-   Difference of two proportions
+
+    -   Randomization test
+    -   Bootstrap confidence interval
+    -   Mathematical model
+
+-   Independence in two way tables
+
+    -   Randomization test
+    -   Bootstrap confidence interval
+    -   Mathematical model
+
 ### [Chp 7. Inference for numerical responses](https://openintro-ims.netlify.app/inference-num.html)
 
-*Complete, exercises need to be formatted*
-
-- One mean
-  - Bootstrap confidence interval
-  - Mathematical model
-- Difference of two means
-  - Randomization test
-  - Bootstrap confidence interval
-  - Mathematical model
-- Paired differences
-  - Randomization test
-  - Bootstrap confidence interval
-  - Mathematical model
-- Comparing many means
-  - Randomization test
-  - Mathematical model
+*Complete, exercises need to be added*
+
+-   One mean
+
+    -   Bootstrap confidence interval
+    -   Mathematical model
+
+-   Difference of two means
+
+    -   Randomization test
+    -   Bootstrap confidence interval
+    -   Mathematical model
+
+-   Paired differences
+
+    -   Randomization test
+    -   Bootstrap confidence interval
+    -   Mathematical model
+
+-   Comparing many means
+
+    -   Randomization test
+    -   Mathematical model
 
 ### [Chp 8. Inference for regression](https://openintro-ims.netlify.app/inference-reg.html)
 
-*In progress*
+*Complete, exercises need to be added*
+
+-   Inference for linear regression
+
+    -   Randomization test
+    -   Bootstrap confidence interval
+    -   Mathematical model
+
+-   Checking model assumptions
 
-- Inference for linear regression
-  - Randomization test
-  - Bootstrap confidence interval
-  - Mathematical model
-- Checking model assumptions
-- Inference for multiple regression
-- Inference for logistic regression
+-   Inference for multiple regression
 
-### Appendix: Probability
+-   Inference for logistic regression
+
+## First edition
+
+**THIS IS A WORK IN PROGRESS!!!**
 
-*The Probability appendix is not yet available for this book. If you would like to learn about probability, we recommend you refer to [OpenIntro Statistics, 4th Edition](openintro.org/book/os).*
+We're currently in the process of finalizing the first edition of Introduction to Modern Statistics.
+It will be available Summer 2021.
 
----
+------------------------------------------------------------------------
 
-Please note that this project is released with a [Contributor Code of Conduct](https://www.contributor-covenant.org/version/2/0/code_of_conduct/). By participating in this project you agree to abide by its terms.
+Please note that this project is released with a [Contributor Code of Conduct](https://www.contributor-covenant.org/version/2/0/code_of_conduct/).
+By participating in this project you agree to abide by its terms.