Samprit Chatterjee & Jeffrey S. Simonoff 
Handbook of Regression Analysis 

A Comprehensive Account for Data Analysts of the Methods and Applications of Regression Analysis.

Written by two established experts in the field, the purpose of the Handbook of Regression Analysis is to provide a practical, one-stop reference on regression analysis. The focus is on the tools that both practitioners and researchers use in real life. It is intended to be a comprehensive collection of the theory, methods, and applications of regression methods, but it has been deliberately written at an accessible level.

The handbook provides a quick and convenient reference or ‘refresher’ on ideas and methods that are useful for the effective analysis of data and its resulting interpretations. Students can use the book as an introduction to and/or summary of key concepts in regression and related course work (including linear, binary logistic, multinomial logistic, count, and nonlinear regression models). Theory underlying the methodology is presented when it advances conceptual understanding and is always supplemented by hands-on examples.

References are supplied for readers wanting more detailed material on the topics discussed in the book. R code and data for all of the analyses described in the book are available via an author-maintained website.

‘I enjoyed the presentation of the Handbook, and I would be happy to recommend this nice handy book as a reference to my students. The clarity of the writing and proper choices of examples allows the presentations ofmany statisticalmethods shine. The quality of the examples at the end of each chapter is a strength. They entail explanations of the resulting R outputs and successfully guide readers to interpret them.’ American Statistician

关于作者

SAMPRIT CHATTERJEE, Ph D, is Professor Emeritus of
Statistics at New York University. A Fellow of the American
Statistical Association, Dr. Chatterjee has been a Fulbright
scholar in both Kazakhstan and Mongolia. He is the coauthor of
Regression Analysis by Example, Sensitivity Analysis in
Linear Regression, and A Casebook for a First Course in
Statistics and Data Analysis, all published by Wiley.

Jeffrey S. Simonoff, Ph D, is Professor of
Statistics at the Leonard N. Stern School of Business of New York
University. He is a Fellow of the American Statistical Association,
a Fellow of the Institute of Mathematical Statistics, and an
Elected Member of the International Statistical Institute. He has
authored or coauthored more than ninety articles and five books on
the theory and applications of statistics.