Items related to Linear Models
Synopsis
This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.
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From the Publisher
The main objective of this text is to describe general procedures of estimation and hypothesis testing for linear statistical models and shows their application for unbalanced data (i.e., unequal-subclass-numbers data) to certain specific models that too often arise in research and survey work. There is a special emphasis on unbalanced data. Exercises are provided throughout the chapter that will enable the reader to practice and become familiar with the techniques described.
About the Author
Shayle R. Searle, PhD, is Professor Emeritus in the Department of Biological Statistics and Computational Biology at Cornell University. Dr. Searle is the author of Linear Models, Linear Models for Unbalanced Data, Matrix Algebra Useful for Statistics, and Variance Components, all published by Wiley.
"About this title" may belong to another edition of this title.
- PublisherWiley-Interscience
- Publication date1997
- ISBN 10 0471184993
- ISBN 13 9780471184997
- BindingPaperback
- LanguageEnglish
- Number of pages560
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Linear Models
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