# Linear and Logistic Regression in Practical Data Science with R 2nd Edition

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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*.

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