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Applied Regression Analysis and Multivariable Methods
 
 

Applied Regression Analysis and Multivariable Methods [Hardcover]

David G. Kleinbaum (Author), Lawrence L. Kupper (Author), Keith E. Muller (Author), Azhar Nizam (Author)
2.9 out of 5 stars  See all reviews (11 customer reviews)


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Applied Regression Analysis and Multivariable Methods (Duxbury Applied) Applied Regression Analysis and Multivariable Methods (Duxbury Applied) 2.9 out of 5 stars (11)
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Book Description

September 15, 1997 0534209106 978-0534209100 3
Regression students will appreciate this best-seller's modern, practical approach and its use of real-life problems. The third edition offers a significant shift in emphasis from calculation to interpretation, by replacing computational formulas with computer printouts in SAS®. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that can be solved with the computer. Appropriate for statistics, biostatistics, mathematics, psychology, sociology, business, and industrial engineering students or anyone who intends to use regression analysis in their work, this text offers a traditional structure with a modern flavor. The authors emphasize model development; the intuitive logic and assumptions that underlie the techniques covered as well as the purposes, advantages and disadvantages, and valid interpretations of those techniques.

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Editorial Reviews

Review

"The authors' writing style is right on the mark--not too many words pass before a good numerical example appears."

"The integration of the software output is well done. Good, motivating, real-life examples and problem sets....Chapter 16 does an excellent job of laying out the problem of selecting the 'best' regression model in a step-by-step manner and brings in variable selection procedures."

"The solution manual to the book is a tremendous 'gift' as it saves a great deal of time for many busy professors."

Product Details

  • Hardcover: 816 pages
  • Publisher: Duxbury Press; 3 edition (September 15, 1997)
  • Language: English
  • ISBN-10: 0534209106
  • ISBN-13: 978-0534209100
  • Product Dimensions: 9.3 x 7.4 x 1.4 inches
  • Shipping Weight: 3.1 pounds
  • Average Customer Review: 2.9 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #446,101 in Books (See Top 100 in Books)

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Customer Reviews

11 Reviews
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Average Customer Review
2.9 out of 5 stars (11 customer reviews)
 
 
 
 
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9 of 9 people found the following review helpful:
5.0 out of 5 stars Super Book, December 18, 2003
By 
Daryl Paulson (Bozeman, Montana) - See all my reviews
(REAL NAME)   
This review is from: Applied Regression Analysis and Multivariable Methods (Hardcover)
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.
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14 of 16 people found the following review helpful:
5.0 out of 5 stars Excellent Introduction to Linear Regression, March 25, 2002
By 
P. Barriga (Montreal Quebec Canada) - See all my reviews
(REAL NAME)   
This review is from: Applied Regression Analysis and Multivariable Methods (Hardcover)
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?)

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13 of 17 people found the following review helpful:
1.0 out of 5 stars waste of money, September 25, 2005
Only the questions with answers in text have solutions. Solutions not complete enough to help if you are having trouble with the concept. Very disappointing, big waste of money. Useless. Wish I could return it
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