R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes:
The term "environment" is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.
Many users think of R as a statistics system. We prefer to think of it of an environment within which statistical techniques are implemented. R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.
Getting R
Is very easy. In Linux systems just type:
sudo apt-get install r-base-core
in your terminal.
Alternatively you can install R via the software repositories
In both Linux and Windows you can try R-Studio, a GUI-style R with split windows holding history, plots and file separately for advanced control (at a certain expense of speed and memory)
Get it here: http://www.rstudio.com/
By downloading it via this link: http://www.rstudio.com/products/rstudio/download/
Running R
Is even easier. In Linux you simply type:
R
in your terminal and the environment loads automatically. You can now start working
R-Studio starts either via the command line or by clicking the approprate button on your programs folder.
Documentation. Getting help
R is open source, which makes it very easy to access the necessary information. There is a great number of online manuals and free books for using and programming R. The R development team has an extended list here
http://www.r-project.org/doc/bib/R-books.html
The standard documentation for each function pops up in R simply by typing
?nameoffunction
or, in case the function is not installed, you can get additional info on packages and modules by typing:
??nameoffunction
When everything else fails you can seek expert advise online in the R-help and R-devel mailing lists as well as in various fora (e.g. http://stackoverflow.com/ etc). Plus there is always google.