The R primer, by Claus Thorn Ekstrom, Boca Raton, Chapman & Hall/CRC Press, 2011, xii+287 pp., £25.99 or US$39.95 (paperback), ISBN 978-1-4398-6206-3
This book provides a good introduction to R, using a clear layout and detailed, reproducible examples. An ideal tool for any new R user.
R is a software that is frequently used by statisticians, for performing calculations or graphical summaries, which can be rather daunting initially. The book is intended for use by newcomers to R. It logically begins with detailed steps for how to read data into R from a variety of sources. Each chapter is divided into sections which are enticingly short, yet sufficiently detailed. Throughout the book there are simple, annotated examples which could easily be applied for practise and then extended for the reader's specific needs. The book nicely flows, introducing topics in such a way that the reader can simply work through the chapters, grasping the basics of R for future use and long-term development. However, each section is also self-contained, enabling the more experienced reader to merely jump to the required section to gain the skills required to run one analysis for a given problem. A wide range of topics are covered, making the book suitable for a variety of readers, from undergraduate students to professionals new to R. The topics may be similar to those found in a typical statistics undergraduate degree. The same structure is used throughout the book, where a problem is presented and a solution suggested, along with a reproducible example. This results in an easy to digest, visually appealing layout. The book is written using statements, which ensure fast, clear solutions to the problems covered, without being too descriptive. However, there are minor grammatical errors which appear unusual, but which thankfully do not detract from the usefulness of the book.
The author aims to provide a user-friendly introduction for newcomers to R, covering frequently encountered problems using examples. It does not aim to cover all areas of R, but instead provides the basics which can be used to develop skills. It usefully refers to extensions or other similar sections in the book, which can be used to further learning. Additional support is also available on the corresponding website. These aims are well met in the book, making it useful for anyone encountering R for the first time or, alternatively, someone wishing to gain the basics of an unfamiliar topic.
This book may be a suitable purchase for a newcomer requiring a range of R skills, who benefits from learning through examples. However, it is not intended to provide any statistical theory, since this is assumed already, nor R programming, which can be viewed as more advanced. It may be also recommended to libraries since it could be used by a range of different professionals from a variety of backgrounds, who may wish to read the entire book or simply use one section to aid their analysis. Overall, an extremely helpful introduction to a very useful statistical package.