Previous edition: Sebastapol, Calif.: O'Reilly, 2010

R BASICS. Getting and installing R -- The R user interface -- A short R tutorial -- R packages -- THE R LANGUAGE. An overview of the R language -- R syntax -- R objects -- Symbols and environments -- Functions -- Object-oriented programming -- WORKING WITH DATA. Saving, loading, and editing data -- Preparing data -- DATA VISUALIZATION. Graphics -- Lattice graphics -- ggplot2 -- STATISTICS WITH R. Analyzing data -- Probability distributions -- Statistical tests -- Power tests -- Regression models -- Classification models -- Machine learning -- Time series analysis -- ADDITIONAL TOPICS. Optimizing R programs -- Bioconductor -- R and Hadoop -- Appendix: R reference

When professionals are faced with analyzing moderate-to-large data sets, tools like Excel do not have the power or flexibility. R was designed for these situations, with good graphical capabilities and a large, robust library of contributed packages. While most books on R are stiff and academic, this Nutshell guide offers a readable overview of R, and contains a reference for the most commonly used features

"A desktop quick reference"--Cover

"Updated for R 2.14 and 2.15 ... includes expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop"--P. [4] of cover