Applied Regression Including Computing and Graphics (Wiley Series in Probability and Statistics) [Hardcover]

R. Dennis Cook (Author), Sanford Weisberg (Author)

Book Description

ISBN-10: 047131711X | ISBN-13: 978-0471317111 | Publication Date: August 6, 1999 | Edition: 1

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.

Editorial Reviews

Review

"...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)

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Product Details

• Hardcover: 632 pages
• Publisher: Wiley-Interscience; 1 edition (August 6, 1999)
• Language: English
• ISBN-10: 047131711X
• ISBN-13: 978-0471317111
• Product Dimensions: 9.6 x 6.4 x 1.3 inches
• Shipping Weight: 2.2 pounds (View shipping rates and policies)
• Average Customer Review: 3.1 out of 5 stars  See all reviews (7 customer reviews)
• Amazon Best Sellers Rank: #649,719 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

25 of 28 people found the following review helpful:

5.0 out of 5 stars regression through graphics, February 9, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Applied Regression Including Computing and Graphics (Wiley Series in Probability and Statistics) (Hardcover)

Ray Carroll and David Ruppert are well known research statisticians who have published many joint articles on regression, weighted regression and transformation and they have also written an excellent book together on this research topic. Stefanski has recently published several papers on measurement error models with Carroll. Here they have teamed up to write a statistics text on a unique topic. Measurement error models are common and practical when dealing with covariates that have measurement error. Least squares estimation in linear regression is based on the assumption that the predictor variables are measured without error. There are many articles and an excellent text by Fuller "Measurement Error Models", published by Wiley in 1988 that deals with the linear case. Also look at a section in Chapter 5 of Miller's "Beyond ANOVA, Basics of Applied Statistics" that refers to the problem as the error in variables problem. For the nonlinear case this is the first treatment. Well written and well documented, this text provides an up-to-date account of the theory and methods and provides real applications (e.g. the Framingham Heart Study). This is a great reference as are many of the other monographs in this series by Chapman and Hall/CRC Press. Includes bootstrap approaches in the chapter on fitting methods and models.

13 of 13 people found the following review helpful:

5.0 out of 5 stars Excellent text, October 27, 2000

By A Customer

This review is from: Applied Regression Including Computing and Graphics (Wiley Series in Probability and Statistics) (Hardcover)

I used Cook/Weisberg's book to teach a required graduate data analysis class. Students found the text easy to understand. In previous classes they had used S-Plus; they raved about how easy ARC was to use --- especially since they could download it for free and use it after graudation without licensing. I found the statistics and mathematics clearly presented and the examples useful. Several of the students used ARC for the data analysis for their theses.

This is a great teaching book with a fabulous software package supporting it, by two of the best statisticians in the world.

I disagree strongly with the previous reviewer: this is much much more than a software manual. It is first a world class regression text, and secondly it supports the new methods with first-rate freeware. Who could complain?

Disclaimer: I studied under both Cook and Weisberg at Minnesota, have taught using previous versions of their books, and contributed data sets for this book.

5 of 6 people found the following review helpful:

5.0 out of 5 stars Applied Regression Including Computing and Graphics (Wiley S, December 21, 2000

By A Customer

This review is from: Applied Regression Including Computing and Graphics (Wiley Series in Probability and Statistics) (Hardcover)

When you touch the cover of the book, you feel the recent trend of regression. I bet you will and you should. It covers most of recent topics in 90's. ARC is a superb software and it provides so many excellent features and tools to look into the real aspects of data analysis. It is also easy enough for beginners to follow the steps.

I tried this for the textbook for my class last semester. My students loved it so much that some of them decided to pursue their career as a statistician.

But many statisticians don't appreciate what is the real value of the book. Too bad.