PDF Ebook Applied Linear Statistical Models (McGraw-Hill/Irwin Series Operations and Decision Sciences), by Michael H Kutner, Christopher J. Nachtsh
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This new edition of Applied Linear Statistical Models retains the book's uniquely straightforward writing style and format while providing you with the latest information and knowledge. Updates include developments and methods in partial regression and residual plots, an entirely new introduction to the "Design of Experiments" section that frames and outlines the organization and concepts of design and ANOVA, and more.
- Sales Rank: #190396 in Books
- Brand: McGraw-Hill Irwin
- Published on: 2004-08-13
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 9.40" h x 2.10" w x 7.50" l,
- Binding: Hardcover
- 1424 pages
About the Author
Michael H. Kutner is a professor at Emory University in Atlanta.
Chris J. Nachtsheim is a professor at the University of Minnesota at Minneapolis.
John Neter is a professor at the University of Georgia in Athens.
Most helpful customer reviews
0 of 0 people found the following review helpful.
The examples in the book are thorough and easy to follow
By zach
This book covers so much knowledge. The book takes an algebraic approach to most topics and shies away from the matrix algebra approach used by so many other books. The examples in the book are thorough and easy to follow. This book is really only about linear regression and ANOVA (one-way, two-way, MANOVA, mixed effects, etc.) models with a few other topics thrown in. The book is organized well and thorough.
The only pitfall is it uses MINITAB. I wish it used R instead.
1 of 1 people found the following review helpful.
I'm only into chapter 2 and I really like the way the book is laid out
By Richard U. Newell
I'm only into chapter 2 and I really like the way the book is laid out. Good examples and clear explanations and proofs regarding what is going on. I agree with other reviewers that you are going to want to take an introductory statistics class at a minimum, and preferably including some calculus-based probability. But once you have that background, this book will help you get to the next level. If anyone refers to this as a statistical "bible", they aren't kidding.
3 of 3 people found the following review helpful.
Explains things well
By Cory Holbein
This book may be a little old, but the clarity and explanations that this book gives can't be beat. If you want an intermediate applied textbook, I'd recommend this one. It covers a lot of types of Regression, such as linear, Logistic, and Poisson. It also covers one-way ANOVA, multi-way ANOVA, ANCOVA, and much more. It also talks about mixed and Random models. I'm still reading, but what I have read is very good.
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