A Beginner’s Guide to R

Book info : Alain F. , Elena N. , and Erik H.W.G. . New York, NY: Springer, 2009. ISBN 978-0-387-93836-3. xv + 218 pp. $59.95 (P).

A Beginner’s Guide to R is just what it’s title implies, a quick-start guide for the newest R users. A unique feature of this welcome addition to Springer’s Use R! series is that it is devoted solely to getting the user up and running on R. Unlike other texts geared towards R beginners, such as Verzani (2005), this text does not make the mistake of trying to simultaneously teach statistics. The experienced R user will not have much use for this book, except perhaps for adoption as a textbook. To this end, there are straightforward homework exercises provided throughout (no answers, though), and the data sets can be downloaded from the authors’ website http://www.highstat.com. It should be noted, however, that the examples and exercises are limited to the authors’ area of expertise – ecology.

The book starts at the very beginning by instructing the user how to install R and load packages from CRAN. One small weakness is that the book is directed almost exclusively toward PC users. In particular, I was disappointed by the paucity of information concerning R text editors that are compatible with the Mac. (After a fair amount of trial and error, I finally determined that gedit would do the job for me.) A nice feature of Chapter 1 is an annotated bibliography of "must-have" R books. Early on, the authors sagely direct the reader toward the universe of R assistance available online (and console the panicked reader that even experienced R users can be intimidated by the sheer amount of information contained in R help files).

The remainder of the book is devoted to demonstrating how to do the most basic tasks with R. Chapter 2 describes several methods for getting data into R (useful information for anybody facing the daunting prospect of importing a large data set into R for the first time). To appease the novice hungering for some "fancy" R output, the authors provide easy-to-follow instructions for constructing both simple (Chapters 5 and 7) and not-so-simple (Chapter 8) graphical displays. Standard plots from the introductory statistics curriculum are included (e.g., the histogram, boxplot, scatterplot, and dotplot), and the lattice package is introduced for the benefit of readers with more advanced graphical needs. Other topics include data management (Chapter 3) and simple functions and loops (Chapters 4 and 6). Chapter 9 concludes the book by suggesting solutions to some problems commonly encountered by R users, beginners and old pros alike.

In sum, A Beginner’s Guide to R is an essential resource for the R novice, whether an undergraduate learning statistics for the first time or a seasoned statistician biting the bullet and making the switch to R. To get the most bang for the buck (the cost is a bit steep for such a short paperback), I advise the user to set aside a weekend (or a week) to launch R and work through the book from start to finish. It will be time well spent — just keep in mind that this book is all about learning to play a scale; you’ll be disappointed if you expect to emerge with all the skills required to perform a concerto.

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