R is a very powerful programming language and environment for statistical computing and graphics. This page presents several courses and training materials that I have prepared about different aspects of R. In the last section, you can also find links to many useful R resources and training material available in the Web.

R is also multiplatform. You can install R in Linux, MacOS or Windows. Additionally, you can also use more advanced GUIs for R, like RStudio (recommended) or Rcmdr (also quite popular, by John Fox). Finally, if you are interested in data mining, make sure you take a look at Rattle, a convenient GUI to explore the many data mining capabilities implemented in R.

An important advantage of R is the very long list of contributed packages that extend the basic functionality in R to implement most of the well-known (and rare) statistical techniques used today. The Comprehensive R Archive Network lists +3,800 packages, and it keeps growing very fast. Since R is libre software, and many brilliant statisticians and programmers are behind the development of these packages, it reassures you to have efficient and reliable implementations for any statistical tool of your choice. Under the hood, many lines of its source code are written in C and Fortran.

Training courses

An brief introduction to R

This video and slides cover a 1h session presenting a brief introduction to R.

• Slides [PDF].
• Video (in Spanish).

Workshop on R and data visualization (Visualizar 2011, @Medialab Prado)

This is a 3h workshop presenting an introduction to basic aspects of R (installation, packages, help, loading and working with data) and graphics (basic graphics, and some examples with multivariate visualization libraries, such as lattice).

• Slides [PDF].
• Data files (various formats).

Workshop on Wikipedia data analysis (Wikipedia Academy 2012, June29, Berlin)

New On June 29, 2012 I delivered a 3h workshop focused on Wikipedia data analysis and my new project, WikiDAT. However, information and code can be useful for researchers and data analysts in different fields. My intention is to progressively incorporate up-to-date tools, techniques and example analyses (lattice, ggplot2, last updates on survival analysis and inequalities, etc.) in WikiDAT.

Useful references

Search and help

• R mailing list archive: This page provides a useful search interface to seek through the vast archive of R mailing lists. It is very likely that your problem or question has been already asked or solved before, so make sure you check here first before asking the same question again.
• RSeek.org:Useful interface to search through many different R sites. You can also browse code snippets, tasks views, etc. (created by Sasha Goodman).
• R Task views: This should be one of your first resources to find available libraries (CRAN packages) implementing the analysis/tool/method you are looking for. Clearly organized by different tasks and subsections.

R projects and packages

• R-CRAN: The Comprehensive R Archive Network is your primary source to look for new, stable R packages.
• R-Forge: A software forge for R projects and libraries. Stable as well as experimental libraries and work in progress is mixed here, so first read the project page and any documentation you may find.

Blogs and websites

• R-bloggers: This is a planet full of news and tutorials contributed by +350 bloggers.
• Quick-R: Great website about R, it is organized by tasks or type of analysis/model. For each one, you will find a quick introduction to the basic theoretical concepts behind it, examples and R code.
• RDataMining: A huge collection of links, tutorials and slides about data mining tools and models in R. Extremely informative and useful. Maintained by Yanchang Zhao.
• R Graphical Manual: Useful, but not very intuitive at first. You have a legion of graphs solving many common problems, using a variety of R libraries. Search by keyword, package or function name to discover sample images and code related to your own work.
• R Cookbook: Simple receipts for frequent problems in R.
• Lattice: Multivariate data visualization in R: Essential reference for anybody working on multivariate data analysis with R. Lattice is an R package implementing Trellis graphs. You can browse the list of all grahps included in the book, learn the code and select between B/W or color themes.
• ggplot2: This is an R package offering elegant plots based on the grammar of graphics.
• R programming: Wikibooks also have this reference about R programming. Many sections are still work in progress, but those already developed contain useful tips and many examples, specially for novel users.

Documents and Journals

• Contributed documents in CRAN: Visit CRAN, click on the contributed link on the left-side panel and explore many useful documents, courses, tutorials and even complete books about R. Some documents available in other languages.
• The R Journal: Official R journal with tons of useful articles, addressing many levels (introductory, intermediate and advanced).
• Journal of Statistical Software: Articles, book reviews, code snippets, and software reviews about algorithms and statistical software, including many articles on R and R libraries.

Books

• Statistics with R: Complete and free book about statistics with R. Includes introductory and advanced topics. HTML and PDF versions available.
• IPSUR: Introduction to probability and statistics using R is another good book, licensed under GFDL.