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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J. Verzani. *em Using R for Introductory Statistics.* Boca Raton FL: Chapman & Hall, 2005.

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Schultz, "A Beginner's Guide to R", The R Journal, 2010

BibTeX citation

@article{RJ-2010-1-book-review, author = {Schultz, Laura M.}, title = {A Beginner's Guide to R}, journal = {The R Journal}, year = {2010}, note = {https://rjournal.github.io/}, volume = {2}, issue = {1}, issn = {2073-4859}, pages = {59-59} }