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Hardcover Applied Regression Including Computing and Graphics Book

ISBN: 047131711X

ISBN13: 9780471317111

Applied Regression Including Computing and Graphics

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Book Overview

Mit Hilfe der Regressionsanalyse versucht man, einen Zusammenhang zwischen einer Systemantwort und einer oder mehreren bestimmenden Variablen zu finden. In den letzten Jahren wurden einige neue Regressionsverfahren entwickelt, die dieses Buch behandelt und - mit der graphischen Analyse als bergeordnetem Aspekt - vergleicht. (10/99)

Customer Reviews

4 ratings

regression through graphics

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.

Applied Regression Including Computing and Graphics (Wiley S

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.

Excellent text

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.

regression emphasizing graphics

Dennis Cook and Sandy Weisberg have written a number of excellent books on regression analysis (jointly and separately). The most recent Wiley books attempt to provide an integrated approach to regression analysis based on graphical methods. Cooks other book deals with the theory. This one is more detailed with examples and is more applications oriented but the philosophy of the two books is the same.
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