[The Art of] Regression and other stories

cross-posted from: https://programming.dev/post/7032449

This will likely be the last (for some time) of my posts about learning resources for Statistical methods and underlying theories for Data Science and Machine Learning foundations.

Regression and Other Stories by Andrew Gelman, Jennifer Hill, and Aki Vehtari, including the ( R ) code and data for the examples.

The author of the linked review seems generally positive about the text, though they noted some concerns.

I’m least likely to use this as my primary resource going forward, in part due due an enthusiastic recommendation for Statistical Rethinking. But it looks like promising supplemental resource to bridge that gap between theory and application.

Please use this as a forum to discuss R, and learn more about it. If you have any questions about how to do specific things in R, this is the place to ask.

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You can download RStudio here. RStudio IDE, which is supported by Posit PBC, is a powerful and well-developed IDE for R. Other development environment options include Emacs addon Emacs Speak Statistics and VSCode.

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Learning resources:

R for Data Science - a good introductory book for learning R. Start here if you’re overwhelmed.
Big Book of R - collection of more than 500 online books/tutorials covering various aspects of R. Some links are to paid books with previews, but most links are to free online textbooks.

[The Art of] Regression and other stories(xianblog.wordpress.com)

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