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More About This Textbook
Overview
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.
Editorial Reviews
Robert W. Hayden
"The text is very clearly written. It contains much wisdom and useful hints for those trying to analyze data with R."Product Details
Meet the Author
John Fox is the Senator William Mc Master Professor of Social Statistics in the Sociology Department of Mc Master 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.
Table of Contents
Preface
1. Getting Started With R
2. Reading and Manipulating Data
3. Exploring and Transforming Data
4. Fitting Linear Models
5. Fitting Generalized Linear Models
6. Diagnosing Problems in Linear and Generalized Linear Models
7. Drawing Graphs
8. Writing Programs
References
Author Index
Subject Index
Command Index
Data Set Index
Package Index
About the Authors