If you are looking for a free R Manual in german language, check out my Book. The PDF-Version has about 450pages.

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.

cross-posted from: https://programming.dev/post/6990204

Richard McElreath has made his course materials available on GitHub.

However, the course follows the 2nd edition of McElreath's book Statistical Rethinking which is not available in a free digital format.

After watching the first lecture in the Statistical Rethinking 2023 YouTube Playlist, I might go ahead and purchase the text and use this course instead of Trevor Hastie and Rob Tibshirani's An Introduction to Statistical Learning (with Applications in R or Python) course.

I also like that this resource has made an explicit attempt to provide code examples in Julia as well as the more popular Python and R.

I wasn't sure who Richard McElreath was so I did a quick search which revealed his position as Director of the Department of Human Behavior, Ecology and Culture at the Max Planck Institute for Evolutionary Anthropology in Leipzig.

cross-posted from: https://programming.dev/post/6942085

Book (Free)

The resource on statistical methods recommended to me the most has been An Introduction to Statistical Learning (with Applications in R or Python) by Gareth James, Daniela Witten, Trevor Hastie, Rob Tibshirani, and Jonathan Taylor. Its free to download and has been kept up to date. (The latest edition is from 2022.)

Online Course (Free with optional payment for "Verified Track")

For those that prefer a structured online course StanfordOnline: Statistical Learning with R by Trevor Hastie and Robert Tibshirani uses An Introduction to Statistical Learning (with Applications in R) as the course textbook.

More In-Depth Book

Individuals with advanced training in the mathematical sciences may wish to use The Elements of Statistical Learning (Data Mining, Inference, and Prediction) by Trevor Hastie, Robert Tibshirani, and Jerome Friedman which provides a more comprehensive and detailed treatment of a wider range topics in statistical learning.

If you, like me, maintain any package in CRAN with Rcpp dependency, be aware checks in R-devel are failing. The fix is simple (is in the bug report linked), but, at least in my case, must be done before 12/12 or the packages will be removed from CRAN.