Variations on Split Plot and Split Block Experiment Designs
Language: English
Published by John Wiley and Sons Ltd, 2007
- First Edition
- Hardcover
- New

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AbeBooks seller since February 27, 2001
Condition: New
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- Title
- Variations on Split Plot and Split Block Experiment Designs
- Author
- Walter T. Federer
- Publisher
- John Wiley and Sons Ltd
- Publication year
- 2007
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 047008149X
- ISBN 13
- 9780470081495
- Edition
- 1st Edition
Variations on Split Plot and Split Block Experiment Designs provides a comprehensive treatment of the design and analysis of two types of trials that are extremely popular in practice and play an integral part in the screening of applied experimental designs--split plot and split block experiments. Illustrated with numerous examples, this book presents a theoretical background and provides two and three error terms, a thorough review of the recent work in the area of split plot and split blocked experiments, and a number of significant results.
Written by renowned specialists in the field, this book features:
* Discussions of non-standard designs in addition to coverage of split block and split plot designs
* Two chapters on combining split plot and split block designs and missing observations, which are unique to this book and to the field of study
* SAS? commands spread throughout the book, which allow readers to bypass tedious computation and reveal startling observations
* Detailed formulae and thorough remarks at the end of each chapter
* Extensive data sets, which are posted on the book's FTP site
The design and analysis approach advocated in Variations on Split Plot and Split Block Experiment Designs is essential in creating tailor-made experiments for applied statisticians from industry, medicine, agriculture, chemistry, and other fields of study.
"Synopsis" may belong to another edition of this title.
About the Author
FREEDOM KING, PHD, is Teaching Support Specialist in the Department of Biological Statistics and Computational Biology at Cornell University. His areas of interest include generalized linear mixed models, experimental designs, categoricaldata analysis, and statistical computing with an emphasis on work sales through SAS® programming techniques.
"About the title" may belong to another edition of this title.
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