R! Books

R! Books

• Oscar: Big Book of R collection
• RStudio: Cheatsheets
• W.N. Venables. An Introduction to R
• Hadley Wickham & Garrett Grolemund (2017). R for Data Science
• Hadley Wickham. Advanced R
• Winston Chang: R Graphics Cookbook, 2nd
• Christoph Hank: Introduction to econometrics with R
• Neale Batra: R for applied epidemiology and public health
• David Dalpiaz: Applied Statistics with R (HTML version) GitHub
• Colin Gillespie. Efficient R programming
• Hadley Wickham (2015). R Packages
• Yihui Xie. bookdown: Authoring Books and Technical Documents with R Markdown
• Yihui Xie. R Markdown: The Definitive Guide
• Julia Silge: Text Mining with R
• Patrick Burns (2011). The R Inferno
• Daniel Navarro. Learning Statistics with R
• Trevor Hastie, Robert Tibshirani, Gareth James, Daniela Witten: An Introduction to Statistical Learning, with Applications in R 2nd. (pdf) with the excellent self-paced video training course. (here is the 15-hours of video training video abstracted by the Data School (YouTube))
• Trevor Hastie (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction
• Norman Matloff. The Art of R Programming (part)
• Michael Crawley (2007). The R Book
• Bolker (2007).Ecological models and data in R (2007 draft). Appendix (w/ delta method)
• Winston Chang. Cookbook for R
• Verzani. simpleR - Using R for Introductory Statistics 
• Kerns. Introduction to Probability and Statistics Using R
• Peng. R Programming for Data Science, The Art of Data Science, Exploratory Data Analysis with R
• Yakir. Introduction to Statistical Thinking (With R, Without Calculus) 
• Aragón. Population Health Data Science with R
• 赵鹏, 谢益辉, 黄湘云 现代统计图形 (Modern Statistical Graphics)