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Applied Regression Analysis and Other Multivariable Methods, by David G. Kleinbaum, Lawrence L. Kupper, Keith E. Muller, Azhar Nizam
Download Ebook Applied Regression Analysis and Other Multivariable Methods, by David G. Kleinbaum, Lawrence L. Kupper, Keith E. Muller, Azhar Nizam
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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.
- Sales Rank: #1020483 in Books
- Brand: Brand: Duxbury Press
- Published on: 1997-09-15
- Original language: English
- Number of items: 1
- Dimensions: 9.50" h x 7.75" w x 1.50" l,
- Binding: Hardcover
- 798 pages
Features
- Used Book in Good Condition
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."
Most helpful customer reviews
7 of 10 people found the following review helpful.
Very confusing
By Peachbulb
I am lucky that I had such a great professor for my statistics class. Unfortunately, although he's great at teaching the material in class, he doesn't have great acumen in choosing textbooks. This book honestly made me way more confused than I otherwise would have been and is one of the worst textbooks I've ever had. First, the layout jams a lot of formulas without giving you enough specifics on how and when to apply them. Second, the authors have a talent for making straight forward stuff confusing.
Case in point is the section on assumptions about error distributions that need to be satisfied in order to do most regression analysis. Among those assumptions are equal variance and normality. These are not hard to represent in a diagram. Yet the diagram the authors provide shows an example of a case in which some, but not all, of the assumptions are violated. Furthermore, it doesn't say in the caption which ones are violated and which ones are not. In fact, it doesn't even mention in the caption that there are some violations. There's a short line in the text that tells you that. It would have been much clearer to present either a picture of a case in which all assumptions are violated, or one in which no assumptions are violated. And it would have been tremendously helpful to make that clear in the caption. As a caveat, I should mention that I used the second edition instead of the third, so this particular diagram may have been changed. But my classmates who used the third edition despised it as much as I did, so I suspect that many of my comments still apply.
I ended up finding a similar book in the library by Terry Dielman and using that instead. That book covered basically the same material but was far better organized and practical.
15 of 17 people found the following review helpful.
Excellent Introduction to Linear Regression
By P. Barriga
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?)
6 of 11 people found the following review helpful.
Not that great
By Student T
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.
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