Using R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldly software documentation and vast number of add-on packages. Organized by short, clear descriptive entries, the book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods, and the creation of graphics.Through the extensive indexing, cross-referencing, and worked examples in this text, users can directly find and implement the material they need. The text includes convenient indices organized by topic and R syntax. Demonstrating the R code in action and facilitating exploration, the authors present example analyses that employ a single dataset from the HELP study. They also provides several case studies of more complex applications. Datasets and code are available for download on the book's Web site.Helping to improve your analytical skills, this book lucidly summarizes the aspects of R most often used by statistical analysts. New users of R will find the simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.
CITATION STYLE
Boshnakov, G. N. (2012). Using R for data management, statistical analysis, and graphics. Journal of Applied Statistics, 39(6), 1382–1383. https://doi.org/10.1080/02664763.2012.657412
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