R is a language and environment for statistical computing and graphics. R provides an integrated suite of software facilities for data manipulation, calculation and graphical display.  R includes

• an effective data handling and storage facility,
• a suite of operators for calculations on arrays, in particular matrices,
• a large, coherent, integrated collection of intermediate tools for data analysis,
• graphical facilities for data analysis and display either on-screen or on hardcopy, and
• a well-developed, simple and effective programming language based on the S language developed at Bell laboratories.

Obtaining R

R is freely available  from the Comprehensive R Archive Network (CRAN) – a worldwide network of sites that provide an extensive repositories of R packages and resources. Most Linux distributions include packages for R in their package management system.

Packages

Packages provide additional functionality to R.  Packages are contributed by the R user community, and the CRAN repository contains many hundreds of packages. Some you may find of general relevance are

• ggplot2 – an alternate plotting library
• Matrix – dense and sparse matrix calculations
• ade4 – analysis of ecological data
• vegan – community ecology
• multcomp – multiple comparisons
• akima – bicubic interpolation
• maps, mapproj, mapdata – packages for mapping

Web Resources

There is a huge variety of R resources available on the web.  You may be interested in

• R-bloggers – an aggregation of R related blogs
• Quick-R – shows many example analyses
• R graph gallery – shows many example plots
• ggplot2 – reference site for the ggplot2 library
• Yeroon – web interface to ggplot2

Books

There are many many books written either specifically for R, or give R examples.  Some popular titles include

• Crawley, M.J., 2007. The R Book, Wiley.
• Fox, J. & Weisberg, H.S., 2010. An R Companion to Applied Regression, Sage Publications.
• Maindonald, J. & Braun, W.J., 2010. Data Analysis and Graphics Using R: An Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics), Cambridge University Press.
• Mittal, H., 2011. R Graph Cookbook, Packt Publishing.
• Pinheiro, J. & Bates, D., 2009. Mixed-Effects Models in S and S-PLUS (Statistics and Computing), Springer
• Venables, W.N. & Ripley, B.D., 2010. Modern Applied Statistics with S (Statistics and Computing), Springer.

In addition, the ever growing UseR! series of books published by Springer contains some excellent titles.