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R is a programming environment that is very much suitable for statistical calculations and creating the graphical representations related to these.
R is freely available for Windows, MacOS and various UNIX variants and is based on the language S.
For this reason it is used in many universities for education and research. New (statistical) techniques developed there are easily implemented in R and made available in the form of packages. A user who wants to use the new technique simply loads the package from the CRAN repository: then the functions and objects related to the technique can be used as standard objects.
So if one is looking for the implementation of a new technique, it is very probable that it is already available in R.
Working with R I use the RStudio IDE (Integrated Development Environment). It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.
It also gives very good support for the work flow that enables creation of dynamic documents: you can intersperse text sections (chunks in the knitr idiom) with R-code chunks and package knitr will execute the R-code and create a document (in pdf, MsWord or html format) where the executed code lines and the results are inserted. Redoing an analysis (for example when new data is available) just means changing the document and running the knitr process without the need for copy and paste of output. See knitr demos or my projects page for examples.

The R Project for Statistical Computing

The official site of 'The R Project for Statistical Computing' with all information and documentation related to R and a link to the 'Comprehensive R Archive Network' (CRAN). R and additional packages can be downloaded from CRAN of one of it mirrors.

Material for R courses

Especially the 'Introduction to R' by Longhow Lam is useful for someone that starts programming R. Here you will find information about the installation and the tools that support the language (e.g. editors that directly interface with R). Also the constructions in the language are described and lots of examples are given. The use of R in solving everyday problems (e.g. classification) is illustrated with small but useful code fragments.


R-Bloggers.com is a central hub of content collected from bloggers who write about R (in English). By viewing this page regularly or subscribing to the RSS feed, one can easily stay informed about developments in the R community and at the same time see of lot of examples of the use of R.

Revolution Analytics

Revolution Analytics (acquired by Microsoft in the first quarter of 2015) offers open source products, services, a free downloadable Revolution R Open and the commercial product Revolution R Enterprise. The company states to add value by providing a more stable platform than the standard open source environment that is rather volatile and by providing performance improvements. About Revolution R Enterprise: "Revolution R Enterprise scales and accelerates R, running R scripts in a high-performance, parallel architecture that supports systems from workstations to clusters and grids including Hadoop and enterprise data warehouses."