One of the chapters that we are especially proud of in Practical Data Science with R is Chapter 7, “Linear and Logistic Regression.” We worked really hard to explain the fundamental principles behind both methods in a clear and easy-to-understand form, and to document diagnostics returned by the R implementations of lm and glm.
For the second edition, we added a new section on regularization of linear models, and how to fit regularized linear models with glmnet.
So if you are looking for a good introduction to the principles and practice of linear models in R, we hope you check out Practical Data Science with R.
Categories: Administrativia Tutorials
Nina Zumel
Data scientist with Win Vector LLC. I also dance, read ghost stories and folklore, and sometimes blog about it all.
Dear blogging colleague, Would you mind sharing an ebook copy of your new book with me?
Our publisher, Manning, has instructions for applying for review copies here: https://www.manning.com/academic. Hopefully they can help you out.