- Hardcover: 688 pages
- Publisher: Duxbury Press; 2 edition (August 13, 1999)
- Language: English
- ISBN-10: 0534368344
- ISBN-13: 978-0534368340
- Product Dimensions: 1.5 x 7.8 x 9.8 inches
- Shipping Weight: 2.7 pounds (View shipping rates and policies)
- Average Customer Review: 3.9 out of 5 stars See all reviews (10 customer reviews)
- Amazon Best Sellers Rank: #464,092 in Books (See Top 100 in Books)
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Design of Experiments: Statistical Principles of Research Design and Analysis 2nd Edition
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The exercises are a great strength of the book. I think the difficulty level, the amount of real data, and the required computer usage are all on target.
I find the book well written, and useful in both a teaching context as well as a consulting one. I find his narrative style in the text, and development of mathematical structures in an appendix at the end of each chapter desirable from a teaching standpoint. The narrative text sets the stage for the mathematical treatment...Kuehl has put the right emphasis on the use of a computer.
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Top customer reviews
The book expects you know some things: Make sure you have a working understanding of things like the General Linear Model; ANOVA; multiple regression; F, Chi-Square, etc. distributions; contrasts; orthogonality; Tukey, Bonfernoni, etc. tests; etc., etc. If you don't have this knowledge, you won't get past the 1st chapters.
The book presents concepts: If you are looking for a practical, how to, step by step approach, this is not the book for you. This book isn't too theoretical either. In a non-engaging manner, the author presents concepts without going through details that you might wish the author would but didn't flesh out. If you have to read this book, hopefully you have prior experience with DOEs or you will struggle to grasp what this author is talking about.
What I liked about the book: In some instances, the author sticks with the same examples for multiple chapters. I like the continuity this gives to the material. The problems at the end of the chapters are kept to a minimum, but maximize the concepts they are testing.
In the end, it is a book that if you are trying to get a Master's degree you will have to take on sooner or later. Hopefully you can add to the book a solid understanding of undergraduate statistics, actual experience performing DOEs, other books that take a different, more student friendly approach, and a good professor. If not, you are in for an uphill battle with this book alone. Good luck!