This page lists resources that I have found very helpful in learning R:

Official R Resources

  • The R Project home page.  You will find official documentation, links to download all versions of R, information about the R contributors and foundation, and much more.
  • The R Journal: The refereed journal with research articles introducing new R packages, updates on news and events, and textbook reviews.
  • The home site for the Bioconductor suite of packages aimed at bioinformatics.

Forums and Mailing Lists

  • The official R mailing lists: R-announce, R-packages, R-help, and R-devel.  There are also many other special interest group (SIG) mailing lists as well.
  • Stack Overflow: An innovative Q&A style forum for programming questions.  You can find questions related to R by putting the tag [r] at the end of a search query.
  • Cross Validated: Another Q&A style forum much like Stack Overflow for statisticians, data analysts, data miners, and data visualization experts.  Many questions about R and other statistical packages appear here.

Online References and Tutorials

  • Rseek: The customized search engine created by Sasha Goodman designed specifically for R related queries.  There is also funcionality for adding Rseek to the available search engines inside Firefox and Internet Explorer.
  • Quick-R: Robert Kabacoff’s excellent overview of how to accomplish tasks like importing and managing data, performing basic and some advanced statistical routines, and how to create basic plots within R.  I find myself accessing this site anytime I need a quick refresher of a concept.
  • R Cookbook: A wiki-style tutorial created by Winston Chang with some excellent examples for manipulating data, statistical analyses, and producing graphics.
  • R Programming: A wikibook of many R topics organized by tasks.  Best of all, anyone can contribute their knowledge of R to this wikibook.
  • Robert Muenchen’s companion reference site to his excellent “R for SAS and SPSS Users” textbook.  This site contains example programs for data management, graphics, statistics, and basic R programming among others.  Also contains a nice table showing which SAS, SPSS, and R packages can be used to accomplish a variety of statistical analyses.
  • R Cookbook by Paul Teetor: A well-written example (recipe) based guide through a wide selection of topics that belongs on any R user’s bookshelf.
  • The Art of R Programming by Norman Matloff: An excellent survey of R that is easily accessible to those with more of a computer science background, and not just statistics. If you are looking to improve the way you develop R scripts, this is a must-have in my opinion!
  • R for SAS and SPSS Users by Robert Muenchen: This is arguably the best textbook for new users of R who have experience using SAS or SPSS.  If you want a preview of the text, Robert has a free PDF version from his earlier notes on using R.
  • ggplot2 - Elegant Graphics for Data Analysis by Hadley Wickham: If you want to truly master creating graphics using the ggplot2 package, this reference from the package’s author tells you how to master the unique language and the many configurations available for ggplot2 graphics.