Applied Regression Including Computing and Graphics

by R. Dennis Cook (The University of Minnesota, St. Paul); Sanford Weisberg (The University of Minnesota, St. Paul)

• ISBN13: 9780470317785
• ISBN10: 0470317787
• Format: eBook
• Copyright: 2009-09-01
• Publisher: Wiley-Interscience

Summary

A step-by-step guide to computing and graphics in regression analysis In this unique book, leading statisticians Dennis Cook and Sanford Weisberg expertly blend regression fundamentals and cutting-edge graphical techniques. They combine and up- date most of the material from their widely used earlier work, An Introduction to Regression Graphics, and Weisberg's Applied Linear Regression; incorporate the latest in statistical graphics, computing, and regression models; and wind up with a modern, fully integrated approach to one of the most important tools of data analysis. In 23 concise, easy-to-digest chapters, the authors present:? A wealth of simple 2D and 3D graphical techniques, helping visualize results through graphs * An improved version of the user-friendly Arc software, which lets readers promptly implement new ideas * Complete coverage of regression models, including logistic regression and generalized linear models * More than 300 figures, easily reproducible on the computer * Numerous examples and problems based on real data * A companion Web site featuring free software and advice, available at www.wiley.com/mathem atics Accessible, self-contained, and fully referenced, Applied Regression Including Computing and Graphics assumes only a first course in basic statistical methods and provides a bona fide user manual for the Arc software. It is an invaluable resource for anyone interested in learning how to analyze regression problems with confidence and depth.

Table of Contents

Looking Forward and Back

Introduction to Regression

Introduction to Smoothing

Bivariate Distributions

Two-Dimensional Plots

Tools

Simple Linear Regression

Introduction to Multiple Linear Regression

Three-Dimensional Plots

Weights and Lack-of-Fit

Understanding Coefficients

Relating Mean Functions

Factors and Interactions

Response Transformations

Diagnostics I: Curvature and Nonconstant Variance

Diagnostics II: Influence and Outliers

Predictor Transformations

Model Assessment

Regression Graphics

Visualizing Regression

Visualizing Regression with Many Predictors

Graphical Regression

Logistic Regression And Generalized Linear Models

Binomial Regression

Graphical and Diagnostic Methods for Logistic Regression

Generalized Linear Models

Appendix

References

Indexes

Table of Contents provided by Publisher. All Rights Reserved.