R is a widely used programming language and software environment for statistical computing and graphics. The software is free, open source and available for Linux, Mac and Windows platforms. The base installation is highly extensible and a huge set (5000+) of contributed packages is freely available for data import and manipulation, visualisation, statistical modelling, and reporting. For computationally-intensive tasks, C, C++ and Fortran code can be linked and called at run time.
The links below point to a selection of (hopefully) usefull resssources to learn and use R. Comments and suggestions are welcome.

Official information/documentation
  • The R-project website
  • The CRAN for R downloads and documentation
  • R manuals edited by the R Development Core Team
  • Task views – lists of useful packages by subject area
  • Packages – full listing of contributed packages
Getting started
There are 100+ books on R programming and its use in applications. Here is a selection of books on R programming:
Many books on applications with R were published by Springer (Use R! series), Chapman & Hall/CRC (the R series), Wiley, and O’Reilly.

Editors and IDEs
R coding style
Getting help
Other ressources
  • The R Journal – journal covering topics that might be of interest to R users/developers
  • useR! – the international R user conference