Introduction to Modern Statistics
Super excited to share the news that Mine Çetinkaya-Rundel and I have finished and published Introduction to Modern Statistics, made possible by @openintroorg.
While we personally love the html version, you can also get the book in pdf or paperback.
One new aspect of the book is a focus on computational methods, presented in parallel to mathematical models. We wrote about the approach here.
But there are so many other fun things about the book… including emphasis on multivariable relationships through data visualization and modeling, case studies, and compelling datasets and examples.
We’ve organized the book into six parts: 1. Intro to data, 2. EDA, 3. regression modeling, 4. foundations of inference, 5. statistical inference, and 6. inferential modeling.
The R Tutorials are written using the learnr package with much of the work due to @baumerben, Andrew Bray, @yabellini, @cantoflor_87, @data_datum.
The R Labs have been recently updated, thanks much to @benjamin_feder.
There are a total of 339 exercises. Answers to the odd questions are at the end of the text, and solutions are available for instructors.
We are extremely appreciative to @MT_statistics, Melinda Yager, and Randy Prium for their valuable feedback and review of the book.
IMS builds on the @openintroorg text: Introduction to Statistics with Randomization and Simulation, written with David Diez and Christopher Barr.
While we know that there is still work to do, we’ve added a first pass of alternative text tags to the diagrams in the html version of the text.
The book uses many of the OpenIntro datasets. The OpenIntro package has recently been updated on CRAN.
The book aligns with many of the OpenIntro education resources.
The source code for the text of the book is available on GitHub.
While the Labs and Tutorials are written in the statistical software R, the text itself is software agnostic and can be used with your favorite classroom statistical software.
For their amazing art and creative vision, we are indebted to Meenal Patel, @iowio, Muge Cetinkaya, and Will Gray.
Thanks @rundel for the many ways you’ve supported the project.
Shout out to #rstats and RStudio (er, posit) for making amazing products on which our work is based.
And last, thanks to @minebocek for writing my favorite exercise of the text:
We hope you enjoy using the text as much as we’ve enjoyed writing it. Have fun!