The R system for statistical computing is an environment for data analysis and
graphics. The root of R is the S language, developed by John Chambers and
colleagues (Becker et al., 1988, Chambers and Hastie, 1992, Chambers, 1998)
at Bell Laboratories (formerly AT&T, now owned by Lucent Technologies)
starting in the 1960ies. The S language was designed and developed as a
programming language for data analysis tasks but in fact it is a full-featured
programming language in its current implementations.
The development of the R system for statistical computing is heavily influenced
by the open source idea: The base distribution of R and a large number
of user contributed extensions are available under the terms of the Free Software
Foundation’s GNU General Public License in source code form. This
licence has two major implications for the data analyst working with R. The
complete source code is available and thus the practitioner can investigate the
details of the implementation of a special method, can make changes and can
distribute modifications to colleagues. As a side-effect, the R system for statistical
computing is available to everyone. All scientists, including, in particular,
those working in developing countries, now have access to state-of-the-art tools
for statistical data analysis without additional costs. With the help of the R
system for statistical computing, research really becomes reproducible when
both the data and the results of all data analysis steps reported in a paper are
available to the readers through an R transcript file. R is most widely used for
teaching undergraduate and graduate statistics classes at universities all over
the world because students can freely use the statistical computing tools.
The base distribution of R is maintained by a small group of statisticians,
the R Development Core Team. A huge amount of additional functionality is
implemented in add-on packages authored and maintained by a large group of
volunteers. The main source of information about the R system is the world
wide web with the official home page of the R project being
http://www.R-project.org
All resources are available from this page: the R system itself, a collection of
add-on packages, manuals, documentation and more.
The intention of this chapter is to give a rather informal introduction to
basic concepts and data manipulation techniques for the R novice. Instead
of a rigid treatment of the technical background, the most common tasks