This book is intended as a guide to data analysis with the R system for statistical computing. R is an environment incorporating an implementation of the S
programming language, which is powerful, flexible and has excellent graphical
facilities (R Development Core Team, 2005b). In the Handbook we aim to give
relatively brief and straightforward descriptions of how to conduct a range of
statistical analyses using R. Each chapter deals with the analysis appropriate
for one or several data sets. A brief account of the relevant statistical background is included in each chapter along with appropriate references, but our
prime focus is on how to use R and how to interpret results. We hope the book
will provide students and researchers in many disciplines with a self-contained
means of using R to analyse their data.
R is an open-source project developed by dozens of volunteers for more than
ten years now and is available from the Internet under the General Public Licence. R has become the lingua franca of statistical computing. Increasingly,
implementations of new statistical methodology first appear as R add-on packages. In some communities, such as in bioinformatics, R already is the primary
workhorse for statistical analyses. Because the sources of the R system are open
and available to everyone without restrictions and because of its powerful language and graphical capabilities, R has started to become the main computing
engine for reproducible statistical research (Leisch, 2002a,b, 2003, Leisch and
Rossini, 2003, Gentleman, 2005). For a reproducible piece of research, the original observations, all data preprocessing steps, the statistical analysis as well
as the scientific report form a unity and all need to be available for inspection,
reproduction and modification by the readers.