A step-by-step guide to computing and graphics in regression analysis<br> <br> 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.<br> <br> In 23 concise, easy-to-digest chapters, the authors present:? A wealth of simple 2D and 3D graphical techniques, helping visualize results through graphs<br> * An improved version of the user-friendly Arc software, which lets readers promptly implement new ideas<br> * Complete coverage of regression models, including logistic regression and generalized linear models<br> * More than 300 figures, easily reproducible on the computer<br> * Numerous examples and problems based on real data<br> * A companion Web site featuring free software and advice, available at www.wiley.com/mathem atics<br> <br> 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.
"...with its up-to-date discussion of regression graphics at a very accessible level, Applied Regression Including Computing and Graphics is a must for everyone working in the area of regression analysis. I strongly recommend it as a text..." (Journal of the American Statistical Association, September 2001)
"...a must for everyone working in the area of regression analysis. I strongly recommend it as a text..." (Journal of the American Statistical Association, September 2001)
Looking Forward and Back.
Introduction to Regression.
Introduction to Smoothing.
Simple Linear Regression.
Introduction to Multiple Linear Regression.
Weights and Lack-of-Fit.
Relating Mean Functions.
Factors and Interactions.
Diagnostics I: Curvature and Nonconstant Variance.
Diagnostics II: Influence and Outliers.
Visualizing Regression with Many Predictors.
LOGISTIC REGRESSION AND GENERALIZED LINEAR MODELS.
Graphical and Diagnostic Methods for Logistic Regression.
Generalized Linear Models.
Series: Wiley Series in Probability and Statistics
Number Of Pages: 632
Published: 6th August 1999
Country of Publication: US
Dimensions (cm): 23.95 x 16.4
Weight (kg): 0.99
Edition Number: 1