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An R Companion to Applied Regression [Paperback]

John Fox , Harvey Sanford Weisberg

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Book Description

Nov 29 2010 141297514X 978-1412975148 2
This is a broad introduction to the R statistical computing environment in the context of applied regression analysis. It is a thoroughly updated edition of John Fox’s bestselling text An R and S-Plus Companion to Applied Regression (SAGE, 2002). The Second Edition is intended as a companion to any course on modern applied regression analysis. The authors provide a step-by-step guide to using the high-quality free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, enhanced coverage of R graphics and programming, and substantial web-based support materials.

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Review

"The text is very clearly written. It contains much wisdom and useful hints for those trying to analyze data with R." -- Robert W. Hayden

About the Author

John Fox is the Senator William McMaster Professor of Social Statistics in the Sociology Department of McMaster University in Hamilton, Ontario, Canada. Professor Fox earned a Ph.D. in sociology from the University of Michigan in 1972. He has delivered numerous lectures and workshops on statistical topics, at such places as the summer program of the Inter-University Consortium for Political and Social Research, the annual meetings of the American Sociological Association, and the Oxford Spring School in Quantitative Methods for Social Research. He has written many articles on statistics, sociology, and social psychology, and is the author of several books on statistics, including most recently Applied Regression Analysis and Generalized Linear Models, Second Edition (Sage, 2008) and A Mathematical Primer for Social Statistics (Sage, 2009), and (with Sanford Weisberg) An R Companion to Applied Regression, Second Edition (Sage, 2011). Professor Fox is an active contributor to the R Project for Statistical Computing and is a member of the R Foundation. His work on this book was partly supported by a grant from the Social Sciences and Humanities Research Council of Canada.

Sanford Weisberg is Professor of Statistics at the University of Minnesota, Twin Cities.  He is also director of the University’s Statistical Consulting Service for Liberal Arts, and has worked with literally hundreds of social scientists and others on the statistical aspects of their research.  Professor Weisberg earned a BA in Statistics from the University of California, Berkeley, and a Ph.D. also in statistics from Harvard University, under the direction of Frederick Mosteller.  The author of more than sixty articles, his research has primarily been in the areas of regression analysis, including graphical methods, regression diagnostics, and statistical computing.  He is a Fellow of the American Statistical Association and former Chair of its Statistical Computing Section.  He is the author or co-author of several books, including Applied Linear Regression (third edition 2005, Wiley), Residuals and Influence in Regression (with R. D. Cook, 1982, Chapman & Hall), Applied Regression Including Computing and Graphics (with R. D. Cook, 1999 Wiley).  He has several publications in areas that use statistics including archeology, plant sciences, wildlife management, fisheries, and public affairs.

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Amazon.com: 3.8 out of 5 stars  5 reviews
16 of 17 people found the following review helpful
5.0 out of 5 stars Excellent, not only for regression models but for R in general Feb 23 2012
By Sitting in Seattle - Published on Amazon.com
Format:Paperback|Amazon Verified Purchase
This book would be a great single volume introduction to R for social scientists and others who do a lot of work with regression models. As may be obvious from the title, it is also a great companion to anyone learning about regression models, e.g., in a statistics course. And if you are more experienced but not deeply knowledgeable about regression diagnostics, you will gain a very solid and valuable grounding in those.

The book has three particularly salient features: (1) the first 150 pages are a very nicely encapsulated introduction to R with hands-on examples that highlight many of the things that are covered in more detail later in the book. If you want to learn R and do regression models, this material is the perfect background. (2) the remainder of the book presents those models in more depth, building up piece by piece and with clear social science examples. Of special note is the attention to regression diagnostics -- which are often mentioned in other texts but not presented in such a practical way as here, with clearly worked examples and interpretations. (3) much of the content relies on the authors' R package "car", which provides a great set of tools for regression models, especially plotting, confidence interval estimation, and model diagnostics.

As an experienced R user, I enjoyed the book more than I expected: it taught me some very useful things about diagnostic tools, and demonstrated the "car" [companion to applied regression] package in a convincing way. I've known about car for years, but hadn't used it much; now I expect to use it regularly, especially for plotting.

Although the book calls itself a "companion" to other texts, it is actually self-contained if you already understand the basics of regression models in general. It avoids mathematical exegesis and focuses instead on exactly how to get things done in R ... and even more importantly, on how to understand what R is doing, how to interpret the results and work with the resulting objects, and how to avoid common problems. I'm going to start highly recommending this text to others who are new to R.
8 of 9 people found the following review helpful
5.0 out of 5 stars Great Value Nov 19 2011
By Amazon User - Published on Amazon.com
Format:Paperback
This is a fantastic book and one of those books that I feel was worth every penny. I bought it to accompany Fox's regression text, so I was disappointed that it didn't correspond perfectly, chapter for chapter. However, it's such a good book that I soon forgave the one drawback. I'll try to update this later on (I took the class last year, so a little hazy on exact points)...I just saw that there were no reviews and wanted to rectify that.
2 of 2 people found the following review helpful
5.0 out of 5 stars Very readable Feb 3 2013
By CD - Published on Amazon.com
Format:Paperback|Amazon Verified Purchase
I was looking for a practical introduction to R in the context of regression analysis. This book is highly readable, providing step-by-step guidance for installing the free R program (for both WIndows and Mac OS). It also provides links and guidance for using the R website. Finally, there is companion site for this book, which provides all the scripts for copying and pasting. Very helpful, even if you prefer typing in commands yourself (error detection).

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