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From the Publisher… This book covers a wide range of topics in both theoretical and applied statistics … the authors list both R and S–PLUS commands and clearly note when a command is applicable only in either S–PLUS or R. Therefore, S–PLUS users also should find this book useful. Detailed executable codes and codes to generate the figures in each chapter are available online at http://www1.appstate.edu/~arnholta/PASWR/front.htm … nicely blend[s] mathematical statistics, statistical inference, statistical methods, and computational statistics using S language ... . Students or self-learners can learn some basic techniques for using R in statistical analysis on their way to learning about various topics in probability and statistics. This book also could serve as a wonderful stand-alone textbook in probability and statistics if the computational statistics portions are skipped.
—Technometrics, May 2009, Vol. 51, No. 2
The book is comprehensive and well written. The notation is clear and the mathematical derivations behind nontrivial equations and computational implementations are carefully explained. Rather than presenting a collection of R scripts together with a summary of relevant theoretical results, this book offers a well-balanced mix of theory, examples and R code.
—Raquel Prado, University of California, Santa Cruz, The American Statistician, February 2009
… an impressive book … Overall, this is a good reference book with comprehensive coverage of the details of statistical analysis and application that the social researcher may need in their work. I would recommend it as a useful addition to the bookshelf.
—Eirini Koutoumanou, University College London, Significance, December 2008