R is flexible, free software ("GNU S") with a plethora of functions, and is widely used amongst statisticians and in many other research areas. It is a dialect of the programming language S and thus related to S-PLUS.
Only in a few points does it differ from S-PLUS; many things are better in R, though there are some areas in which S-PLUS is more suitable (such as the analysis of variance). Those familiar with S-PLUS can easily handle R as well. For a detailled description of R, see the website of The R Project for Statistical Computing.
R is available for UNIX / Linux, Windows and Mac.
A short R tutorial for students with their own computer account at ETH can be downloaded here: for Linux and Emacs, for Windows and TinnR and for RStudio. For a more extensive introduction to R, see the CRAN documentation (Documentation - Manuals).
A classic textbook on the S language (on which R is based) is:
The CRAN network refers to manny other online resources, books and other documentation for R.
The Seminar for Statistics offers consulting services for R.
Since R is the main statistical software used by the Seminar for Statistics, our consulting services are at their best when this software is involved.
The class `Using R for Statistical Data Analysis and Graphics' is taught each autumn semester. The tutorials for `Applied Statistical Regression' (`Angewandte statistische Regression', taught each autumn semester) make intense use of R. An introductory class in statistics is prerequisite for `Applied Statistical Regression', which is designed as an applied class. Furthermore, a class on `Computational Statistics' is taught each spring, using R in its exercises.
There are mailing lists for R users. For more information and to subscribe, see The R Project for Statistical Computing (Mailing Lists). The primary mailing list is called "R-help"; it offers swift and competent answers to problems with R.
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