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Applied Regression Analysis and Multivariable Methods (Duxbury Applied)

Applied Regression Analysis and Multivariable Methods (Duxbury Applied)Authors: David G. Kleinbaum, Lawrence L. Kupper, Azhar Nizam, Keith E. Muller
Publisher: Duxbury Press
Category: Book

List Price: $218.95
Buy Used: $110.00
as of 7/29/2010 07:13 CDT details
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New (20) Used (44) from $110.00

Seller: graceicarter
Rating: 3.0 out of 5 stars 8 reviews
Sales Rank: 87739

Media: Hardcover
Edition: 4
Pages: 906
Number Of Items: 1
Shipping Weight (lbs): 2.8
Dimensions (in): 9.3 x 7.7 x 1.4

ISBN: 0495384968
Dewey Decimal Number: 519.536
EAN: 9780495384960
ASIN: 0495384968

Publication Date: April 23, 2007
Availability: Usually ships in 1-2 business days

Also Available In:

  • Hardcover - Applied Regression Analysis and Other Multivariable Methods
  • Paperback - Applied Regression Analysis and Other Multivariable Methods
  • Paperback - Applied Regression Analysis and Multivariable Methods (AISE)
  • Paperback - Applied Regression Analysis and Other Multivariable Methods
  • Hardcover - Applied Regression Analysis and Other Multivariable Methods (The Duxbury series in statistics and decision sciences)
  • Hardcover - Applied Regression Analysis and Multivariable Methods
  • Hardcover - Applied regression analysis and other multivariable methods

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Editorial Reviews:

Product Description
This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that you can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques.


Customer Reviews:
Showing reviews 1-5 of 8



5 out of 5 stars Super Book   December 19, 2003
Daryl Paulson (Bozeman, Montana)
9 out of 9 found this review helpful

I have used this book from first edition in the early 1980's in grad school to lastest edition in 2003. A very good book, designed to be used with statistical software. The authors understand the field and provide a thorough yet concise perspective of mainly regression and ANOVA models. An absolute must book for the applied statistician.


5 out of 5 stars Excellent Introduction to Linear Regression   March 25, 2002
P. Barriga (Montreal Quebec Canada)
13 out of 15 found this review helpful

I used this book for a second level statistics course for my Master's degree in Epidemiology. I liked it!

All the underlying math you want to know is sitting on the pages, clearly explained though examples with computer output and graphs. I worked through the problems in the text without difficulty and reproduced their work. I understood what I was doing. Each chapter is followed by a series of problems. You probably want to get a solutions manual if you want to check your answers.

The material covered includes: Univariable and multivariable linear regression, correlations including multiple partial, ANOVA, ANCOVA, Polynomial Regression including orthogonal polynomials, dummy variables, selecting best regression equation, and introductions to repeated measures ANOVA, maximum likelihood methods, and logistic regression.

Now that I feel that I have these basics under control, I would like a book on "approaches" to data and dealing with "difficult" data. This book contains one chapter on regression diagnostics -- not enough. But I guess that is the next step....

Other readers have commented on other books addressing the same topic, unfortunately I have not read those other books. However, I am certain that you will learn from this book, and when you are done, you will be ready for more.

(Did I mention that I signed up for a course with Dr. Kleinbaum on analysis of matched data?)


5 out of 5 stars Top of the line for multivariate issues understanding   October 21, 1999
Dino F. Vitale (duilio@unina.it) (Naples, Italy)
12 out of 29 found this review helpful

The most complete and cristal clear exposition of multivariate analisys I ever read.


3 out of 5 stars Not my favorite   October 4, 2001
3 out of 14 found this review helpful

This book skips some important basic concepts and has several poor, glossed-over explantions. I'd recommend Neter or Mendenhall.


2 out of 5 stars Not that great   September 8, 2004
Student T (North Carolina, USA)
6 out of 10 found this review helpful

I was surprised when I took this class that I did not like this book. All of my epid profs highly recommended this text. You have to flip back and forth when you are doing the problems because they list the SAS output that you need once in one chapter. I know it saves space, but this can get maddening. I did not find the examples clearly written at all-the lack of fit test, and some of the stuff about partial F tests could have used a few more sentences.

No, I cannot write a glowing review of the text, but the only reason for the second star is because I also had a terrible instructor for this course. Perhaps if Dr. Kleinbaum had taught this to me, I would have a different perspective of this book. However, I was pretty much teaching myself this material, and this book is not designed for that.


Showing reviews 1-5 of 8



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