Resources For Learning R

Here is a brief list of external resources for learning R.
Many other excellent resources are available besides what I list here, and I encourage you to search for and use them.

Websites

1. An Introduction to R originally by by Bill Venables and David M. Smith in 1990. It’s been maintained and refined by R Core Developers since then.
2. CRAN manuals by R Core Developers. These technical documents are the authoritative source of all things R. When people say, “read the manual”, these are the manuals they’re referring to.
3. Stack Overflow R index page Contains a large list of free resources for learning R. Stack Overflow is a popular Q & A site for programmers. If an answer has a large number of votes, then it’s usually credible.
4. fasteR by Norm Matloff. Another introduction to R.
5. Advanced R by Hadley Wickham. A deeper look into how R works. Quite readable.
6. CRAN task views Curated indexes of R software for specific applications, for example, High Performance and Parallel Computing with R.
7. R for Data Science by Garrett Grolemund & Hadley Wickham. Introduction to the tidyverse and Rstudio IDE.
8. R language definition by R Core Developers. This is for the curious students who want to go deeper than my STAT 128 class and learn the precise semantics of the language.

Books

1. Data Science in R by Deborah Nolan & Duncan Temple Lang. Deep, realistic case studies in data science. I recognize several of these chapters from assignments in Duncan’s graduate level statistical programming class. accompanying website
2. [The Pragmatic Programmer] by David Thomas & Andrew Hunt. Classic text on general best practices for programming, not R specific.