R Statistics

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R is a free software for statistical analysis and graphics.
It runs on various UNIX platforms, Windows, and MacOS.
The latest version 2.4.1 was released on 2006-12-18, rated 4.3 out of 5[1].

screenshot of R running on Unix

What is R?

(Taken from R for beginners)

R is a system for statistical analyses and graphics created by Ross Ihaka and Robert Gentleman. R is both a software and a language considered as a dialect of the S language created by the AT&T Bell Laboratories. S is available as the software S-PLUS commercialized by Insightful2 There are important erences in the designs of R and of S: those who want to know more on this point can read the paper by Ihaka & Gentleman (1996) or the R-FAQ, a copy of which is also distributed with R. R is freely distributed under the terms of the GNU General Public Licence; its development and distribution are carried out by several statisticians known as the R Development Core Team.

R is available in several forms: the sources (written mainly in C and some routines in Fortran), essentially for Unix and Linux machines, or some pre-compiled binaries for Windows, Linux, and Macintosh. The les needed to install R, either from the sources or from the pre-compiled binaries, are distributed from the internet site of the Comprehensive R Archive Network (CRAN) where the instructions for the installation are also available. Regarding the distributions of Linux (Debian, . . . ), the binaries are generally available for the most recent versions; look at the CRAN site if necessary.

R has many functions for statistical analyses and graphics; the latter are visualized immediately in their own window and can be saved in various formats (jpg, png, bmp, ps, pdf, emf, pictex, xg; the available formats may depend on the operating system). The results from a statistical analysis are displayed on the screen, some intermediate results (P-values, regression coef- cients, residuals, . . . ) can be saved, written in a le, or used in subsequent analyses.

The R language allows the user, for instance, to program loops to successively analyse several data sets. It is also possible to combine in a single erent statistical functions to perform more complex analyses. The

R users may benet from a large number of programs written for S and available on the internet6, most of these programs can be used directly with R. At rst, R could seem too complex for a non-specialist. This may not be true actually. In fact, a prominent feature of R is its exibility. Whereas a classical software displays immediately the results of an analysis, R stores these results in an \object", so that an analysis can be done with no result displayed. The user may be surprised by this, but such a feature is very useful. Indeed, the user can extract only the part of the results which is of interest.

Install R

• choose a download mirror: [list of mirror sites for R download]
• download the right package for you (Linux/Windows/Mac)
• install the package following the OS-specific instructions

Links

• home of the R project
• list of mirror sites for R download
• R (Mac build) on versiontracker

• R for beginners by Emmanuel Paradis