Update README

Author: mine-cetinkaya-rundel

README.md

@@ -6,133 +6,6 @@ As we're working on the 2nd edition of this book, we realized that we weren't to
 
 If you're looking for the source files for the 1st edition of OpenIntro - Introduction to Statistics with Randomization and Simulation, please download the zipped release [here](https://github.com/OpenIntroStat/randomization-and-simulation/releases).
 
-## What's planned for Introduction to Modern Statistics?
-
-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.
-
-## Preliminary edition
-
-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
-
-### [Chp 2. Summarizing and visualizing data](https://openintro-ims.netlify.app/summarizing-visualizing-data.html)
-
-*Complete*
-
--   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*
-
--   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)
-
-*Complete*
-
--   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 added*
-
--   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 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 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)
-
-*Complete, exercises need to be added*
-
--   Inference for linear regression
-
-    -   Randomization test
-    -   Bootstrap confidence interval
-    -   Mathematical model
-
--   Checking model assumptions
-
--   Inference for multiple regression
-
--   Inference for logistic regression
-
-## First edition
-
-**THIS IS A WORK IN PROGRESS!!!**
-
-We're currently in the process of finalizing the first edition of Introduction to Modern Statistics.
-It will be available Summer 2021.
-In the meantime, you can follow along with updates to the first edition [here](https://openintro-ims-1e.netlify.app/) however we do not recommend using the in progress version for teaching while it's being updated as we might move around sections content and exercises, which might be unexpected for you and your students.
-
 ------------------------------------------------------------------------
 
 Please note that this project is released with a [Contributor Code of Conduct](https://www.contributor-covenant.org/version/2/0/code_of_conduct/).