There are several publicly available textbook resources on data analysis and learning R written by remarkable researchers.

### Statistical Learning

*An Introduction to Statistical Learning* by Gareth
James, Daniela Witten, Trevor Hastie, and Robert Tibshirani

### The Leanpub website

Leanpub offers various textbooks for free or for a small donation

by Rafael Irizarry and Michael Love*Data Analysis for the Life Sciences*by Roger D. Peng*R Programming for Data Science*by Roger D. Peng*Exploratory Data Analysis with R*by Brian Caffo*Statistical inference for data science*by Jeff Leek*The Elements of Data Analytic Style*by Caffo, Peng, Leek*Executive Data Science*by Peng, Sean Kross, Brooke Anderson*Mastering Software Development in R*by Caffo, Kross*Developing Data Products in R*

### Graphing

*R Graphics Cookbook*by Winston Chang*ggplot2: Elegant Graphics for Data Analysis** by Hadley Wickham*Developing Data Products*by Brian Caffo and Sean Kross

### Hadley Wickham

Hadley Wickham the chief scientist at
RStudio has contributed numerous
packages to the R community. In addition to his *ggplot2* textbook, he has
written other resources for data science and advanced topics in R.

### Efficient R Programming

Written by Colin Gillespie and Robin Lovelace, the **Efficient R Programming**
textbook provides good reference for advanced topics in R.

*Book compilation required from GitHub. See the GitHub README on the repo.

### Reference

A practical reference textbook for basic statistical analyses.

by Torsten Hothorn and Brian S. Everitt*A Handbook of Statistical Analyses using R (Ed. 3)*