This is a short guide to introductory sources for using the R language for Statistical Computing

R is a environment and programming language for statistical computing. It features built in functions for many statistical techniques and can create very good statistical graphics. One of the great things about R is that it is an open source project, meaning that the software is free to download, use, and extend. R runs on Linux, Mac, and Windows.

R's was built for statistical analyses and graphing. Because of R's extensibility scholars and practitioners in a number of fields are using R for statistics and other data related tasks. To get an idea of what people are doing with R, browse the R-bloggers site.

Below are suggested books, tutorials, and other resources that can help you learn and use R.

Download R from from its maintaining organization CRAN.

RStudio is a popular environment for R. It functions as a wrapper for the language and includes nice features like syntax highlighting and a easy to use graph and package managers. Beginners may find it a little more approachable than base R. Highly recommended for Windows users for aesthetic reasons.

The R Tutorials Series is a nice hands-on set of tutorials focusing on statistical tasks more than the mechanics of the language.

R Tutorial by Chi Yau. This tutorial begins with basic information about how R functions as a language, then quickly moves on to statistical operations such as summary statistics, working with probabilities, and regression. This abridged version is free online.

A Beginner's Guide to R. This eBook provides walk through of the R language focusing on basic tasks like subsetting data, writing functions, and graphing.

Text Analysis with R for Students of Literature. This is a good beginner's tour of R with a focus on literary analysis.

The Use R! series of eBooks from Springer provides in depth information on using R in a variety of fields. Some introductory books are included.

OpenIntro Statistics is set of introductory resources for learning statistics and R at the same time. This resource includes a textbook, labs, example data sets, videos, and forums.

Understanding Statistics with R This book focuses on introductory statistics with examples and exercises in R.

ggplot2 : Elegant Graphics for Data Analysis by Hadley Wickham is a very good introduction to graphics using the popular ggplot2 package. It includes many hands-on examples.

Lattice by Deepayan Sarkar focuses on the popular Lattice graphics package for R.

R can be extended by downloading packages that add more functions to R. Often these packages are designed to make working in a given field easier.

The CRAN Task Views page organizes packages by their purposes such as finance, biostatistics, machine learning etc.

Crantastic offers an option to see packages listed according to popularity

R and RStudio are available on all the computers Gelman Library.

Statistical Programming DC is a local group with a strong R user base.