R Statistics: Difference between revisions
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'''R''' is a free software for statistical analysis and graphics.<br> | |||
It runs on various UNIX platforms, Windows, and MacOS.<br> | |||
The latest version 2.4.1 was released on 2006-12-18. | |||
==What is R?== | ==What is R?== | ||
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Indeed, the user can extract only the part of the results which is of interest. | Indeed, the user can extract only the part of the results which is of interest. | ||
== | ==Install R== | ||
== | ==Tutorials== | ||
==Examples for commonly used | ==Examples for commonly used statistics== | ||
==Bioconductor & Microarray data Analysis== | ==Bioconductor & Microarray data Analysis== | ||
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1. [http://cran.r-project.org/doc/contrib/Paradis-rdebuts_en.pdf R for beginners]. By Emmanuel Paradis | 1. [http://cran.r-project.org/doc/contrib/Paradis-rdebuts_en.pdf R for beginners]. By Emmanuel Paradis | ||
== Links == | |||
* [http://www.r-project.org/ home of the R project] | |||
* [http://cran.r-project.org/mirrors.html list of mirror sites for R download] |
Revision as of 01:34, 26 March 2007
back to stats portal |
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.
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
Tutorials
Examples for commonly used statistics
Bioconductor & Microarray data Analysis
References
1. R for beginners. By Emmanuel Paradis