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 a modern implementation of S, one of several statistical programming languages designed at Bell Laboratories.
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.
Many statisticians use R with the command line. However, the command line can be quite daunting to a beginner of R. Fortunately, there are many different graphical user interfaces available for R which help to flatten the learning curve.
|Graphical User Interfaces for R|
|RStudio||Integrated development environment for R|
|Tinn-R||GUI for R Language and Environment|
|Rattle||Gnome cross platform GUI for Data Mining using R|
|Deducer||Intuitive, cross-platform graphical data analysis system|
|RKWard||Easy to use, transparent frontend|
|JGR||Universal and unified graphical user interface for R|
|RCommander||Commonly known as Rcmdr, a graphical user interface for R|
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Other resources for R: