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About this book
About this book
Comprehensive and engineering-oriented, "Probability and Statistics with R" provides a thorough treatment of probability statistics, clear and accessible real-world examples, and fully detailed proofs. The text step-by-step explains numerous examples in R and S-PLUS for nearly every topic covered, including both traditional and nonparametric techniques. With a wide range of graphs to illustrate complex material as well as a solutions manual, the book also offers an accompanying website that features supporting information, including datasets, functions, and other downloadable material. It is ideal for undergraduate students and for engineers and scientists who must perform statistical analyses.
A Brief Introduction to S. Exploring Data. General Probability and Random Variables. Univariate Probability Distributions. Multivariate Probability Distributions. Sampling and Sampling Distributions. Point Estimation. Confidence Intervals. Hypothesis Testing. Nonparametric Methods. Experimental Design. Regression. Appendices. References. Index.
728 pages, 176 black & white illustrations, 141 black & white tables
! 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