Introductory comments

This text is one of a series of five handbooks that present an overview on how to use a major
statistical software package. Handbooks include S-PLUS, Stata, SPSS, SAS, and R. Although
R is not strictly speaking a statistical package, it is a currently popular statistical language
that is downloaded into ones computer from various mirror sites. It is similar in logic to the
S language of the 1980s, which later became transformed to the S-PLUS commercial package.
Brian Everitt, an Emeritus Professor with the Department of Biostatistics and Computing at
King’s College, London, is the primary author of the series. He is a co-author of each book
in the series, serving as the lead author in several, including the subject text of this review.
Other series authors are uniquely competent in the use of the particular statistical package
of the title.
As other handbooks, this text on R comes in both hardback and paperback. Libraries tend
to purchase the hardback editions, all other tend to prefer the paperback. The list price of
the paperback edition is USD 49.95, but it can be purchased through Amazon or Barnes &
Noble for USD 44.95. This is a reasonable cost for an academic text of 304 pages.
The book has fifteen chapters, each devoted to particular aspect of the software. Each chapter
ends with a list of three to five exercise questions, based on the subject of the related chapter.
The bibliography contains in excess of two hundred entries, providing the reader with an
excellent resource of primary readings.
R’s higher-level computing language and statistical, data management, and graphical capabilities
are outlined in the text. Useful examples are presented to assist understanding. In
addition, examples incorporate the R commands which produce the output of interest. A
package containing the data sets used for examples can be downloaded from the Comprehensive
R Archive Network (CRAN). I shall outline the contents of each chapter, offering
comments along the way.