"The statistical software R has a great many things in its favour:
it is free, open source and versatile, there are many
packages for different applications, and there are graphical
user interfaces such as R Commander or RStudio. However,
as Nicholas J. Horton and Ken Kleinman explain, R software
documentation is 'extensive, idiosyncratic, and sometimes
To solve this problem, and to increase user productivity
when working with R, Horton and Kleinman wrote this book as a
quick-reference guide. It contains both a subject index and
an R functions index, as well as numerous cross-references, to
help readers find the function they need.
The book summarises the main instructions for dealing with
data, the functions for the most common statistical analyses
and two extensive chapters on ggraphics. It will not teach
the reader statistical methods, but it explains how to apply these
methods in R. For more advanced applications, however, users will
still need to refer to R documentation.
Overall, the book is easy to use. I have had it on my desk for the past
few weeks and it has become invaluable. For those, like me,
who find themselves regularly switching between R, Matlab, and
Python - or similar packages - it can save a lot of time."
(Jordi Prats, Significance, February 2016)