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

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


A practical reference textbook for basic statistical analyses.

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