The R language (and open-source software) is the de facto standard among statisticians for the development of statistical software, and is widely used for statistical software development and data analysis.
R is much more than a programming language. It’s an interactive environment for performing statistics. R offers 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 ability to download and install R packages is a key factor which makes R an excellent language to learn. Packages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data. The CRAN package repository hosts over 10,000 packages, and Bioconductor hosts nearly 1,300 packages.
Type of Language: Multi-paradigm: Array, object-oriented, imperative, functional, procedural, reflective
Designed by: Ross Ihaka and Robert Gentleman
Public Release: 1993
License: GNU GPL v2
RECOMMENDED OPEN SOURCE BOOKS
OPEN SOURCE SOFTWARE FOR DEVELOPERS
RStudio – Integrated Development Environment.
CRAN – The Comprehensive R Archive Network.
Bioconductor – Open Source Software for Bioinformatics.
R-Bloggers – an informative blog aggregator of content contributed by bloggers who write about R.
Google’s R Style Guide