Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences)
by Michael H Kutner, Christopher J. Nachtsheim, John Neter
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Book Summary Information
Author: Christopher J. Nachtsheim, John Neter, Michael H KutnerEdition: Hardcover
Audio: English (Original Language); English (Unknown); English (Published)
Published: 2004-01-08
ISBN: 0073014664
Number of pages: 701
Publisher: McGraw-Hill/Irwin
Book Reviews of Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences)
Book Review: Excellent Book for Classes and Self-study
Summary: 5 Stars
I used this book for my statistic class. After thoroughly reading this book, I become quite familiar with the subject matter.
1. The explanations in most parts are so clear and easy to understand. A few small sections are difficult, but they are not essential topics for this book. If you think the book is not intuitive, use Peter Kennedy's A Guide to Econometrics (5th edition) as complementary reading.
2. You can find all the corresponding SAS programs on the Internet. Do the exercises with SAS, otherwise you will learn nothing. If you don't know SAS, read Delwiche and Slaughter's The Little SAS Book (3rd edition) or SAS Online Tutor for Base Programming.
3. If you are not familiar with basic statistic concepts, read the appendices of the book first.
4. The book is sufficient and easily understood for what it contains. If you want more and deeper information, use other books to complement it.
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Summary of Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences)
Thoroughly updated and more straightforward than ever, Applied Linear Regression Models includes the latest statistics, developments, and methods in multicategory logistic regression; expanded treatment of diagnostics for logistic regression; a more powerful Levene test; and more. Cases, datasets, and examples allow for a more real-world perspective and explore relevant uses of regression techniques in business today.
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