R

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.

Availability at ETH Zurich

R is GNU software, and can thus be downloaded free of charge via the Internet, for instance from the ETH mirror of the CRAN network.

Literature

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:

• J.M. Chambers and T.J. Hastie, Statistical Models in S, Wadsworth & Brooks/Cole, 1992 (This is often called the `White book'.)
  (ETH-BIB 755 142)                                                                                
  

The CRAN network refers to manny other online resources, books and other documentation for R.

Consulting and courses

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.

Courses

We offer regular introductory courses for R, in the shape of both full-day training courses for staff and external participants (in German and English) and evening classes for students.

Classes
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.

Hints

User Group

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.

Newsletter
Since January 2001, R has had an online newsletter, which in 2009 became the R Journal.