R in a Nutshell includes a quick introduction to the R statistical software; so if you are new to working with R you can catch up in a few pages. But it also is a full reference for the R programming language and a great variety of R packages which are available.
More in detail, it includes a description of the R syntax, objects, functions, saving and loading data, and graphics as well as more advanced topics like object-oriented programming and high-performance R. The packages that it presents deal with basic statistics, probability distributions, statistical tests, and power tests. The packages for regression models go further to nonlinear models, splines, smoothing as well as machine learning algorithms like neural networks, and support vector machines for regression. The classification models that the book describes include linear models as well as nearest neighbors, random forests and other algorithms. A chapter is devoted to time series analysis.
Finally a complete example is presented for a bioconductor application. I think that the book makes a good desktop quick reference. Of course it does not captures all subjects possible, for example solving ODEs with R is possible, but the variety of R packages are so great that in a book one has to concentrate on the most important parts.
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