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SAGE Publications
An R Companion to Applied Regression / Edition 2

An R Companion to Applied Regression / Edition 2


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An R Companion to Applied Regression / Edition 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.

Product Details

ISBN-13: 9781412975148
Publisher: SAGE Publications
Publication date: 11/29/2010
Edition description: Second Edition
Pages: 449
Sales rank: 489,077
Product dimensions: 6.90(w) x 9.90(h) x 1.10(d)

About the Author

John Fox is professor of sociology at Mc Master University in Hamilton, Ontario, Canada. Fox earned a Ph D in sociology from the University of Michigan in 1972, and prior to arriving at Mc Master, he taught at the University of Alberta and at York University in Toronto, where he was cross-appointed in the sociology and mathematics and statistics departments and directed the university's statistical consulting service. He has delivered numerous lectures and workshops on statistical topics in North and South America, Europe, and Asia, at such places as the summer program of the Inter-University Consortium for Political and Social Research, the Oxford University Spring School in Quantitative Methods for Social Research, and the annual meetings of the American Sociological Association. Much of his recent work has been on formulating methods for visualizing complex statistical models and on developing software in the R statistical computing environment. He is the author and co-author of many articles, in such journals as Sociological Methodology, Sociological Methods and Research, The Journal of the American Statistical Association, The Journal of Statistical Software, The Journal of Computational and Graphical Statistics, Statistical Science, Social Psychology Quarterly, The Canadian Review of Sociology and Anthropology, and The Canadian Journal of Sociology. He has written a number of other books, including Regression Diagnostics (SAGE, 1991), Nonparametric Simple Regression (SAGE, 2000), Multiple and General-ized Nonparametric Regression (SAGE, 2000), A Mathematical Primer for Social Statistics (SAGE, 2008), and, with Sanford Weisberg, An R Companion to Applied Regression, Second Edition (SAGE, 2010). Fox also edits the SAGE Quantitative Applications in the Social Sciences (QASS) monograph series.

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

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
Author Index
Subject Index
Command Index
Data Set Index
Package Index
About the Authors

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