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.