R is an open-source statistics package. It is highly extensible — the core package comes with many statistical routines, R’s functionality can easily be extended by installing optional packages, and the R language can be used to write new packages. From the R Project website:
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 provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.
R is widely used and produces reliable results. It is also cross platform: it runs natively on Mac OS X, Linux and Windows.
R can be downloaded from the website for The R Project for Statistical Computing. To get started using R, visit:
The basics of R are easy to learn for users with some experience using syntax-based statistical software. Nevertheless, R can be extended in many ways, so it is a good idea to consult multiple references when learning or researching functions.
