The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming. The student should have a basic understanding of statistical inference such as contained in "Statistical inference for data science". The book gives a rigorous treatment of the elementary concepts of regression models from a practical perspective. After reading the book and watching the associated videos, students will be able to perform multivariable regression models and understand their interpretations.
This open book is licensed under a Creative Commons License (CC BY-NC-SA). You can download Regression Models for Data Science in R ebook for free in PDF format (4.3 MB).
Table of Contents
Ordinary least squares
Regression to the mean
Statistical linear regression models
Multivariable regression analysis
Multivariable examples and tricks
Residuals, variation, diagnostics
Multiple variables and model selection
Generalized Linear Models
Regression Models for Data Science in R
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