Applied Statistics: Analysis of Variance and Regression / Edition 3

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For the ever-increasing number of practitioners who must perform sophisticated statistical analyses on computers, Applied Statistics: Analysis of Variance and Regression has long been a standard reference and text. This new Third Edition has been thoroughly revised to provide a comprehensive and up-to-date combination of sound statistical methodology, practical advice on the application of this methodology, and interpretation of output from statistical programs.
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Editorial Reviews

From the Publisher
"…beginning level graduate students in statistics will find this book very valuable." (Journal of Statistical Computation and Simulation, January 2006)

"…Overall this is an excellent book…I recommend this book to everyone…" (Statistical Methods in Medical Research, Vol. 14, 2005)

"…The book is an excellent material for describing the data as well as a useful textbook for students to understand, apply and to interpret the statistical methods." (Zentralbaltt MATH, May 2005)

"…it contains a wealth of useful up-to-date information and examples from the health sciences." (Technometrics, November 2004)

"The level of the book is also more consistently intermediate...a few more advanced topics are now excluded." (The American Statistician, August 2004)

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Product Details

Meet the Author

RUTH M. MICKEY, PHD, is Professor of Statistics at the University of Vermont in Burlington.

OLIVE JEAN DUNN, PHD, is Professor Emeritus at the University of California, Los Angeles.

VIRGINIA A. CLARK, PHD, is also Professor Emeritus at the University of California, Los Angeles. Drs. Dunn and Clark are the authors of Basic Statistics: A Primer for Biomedical Sciences, Third Edition, published by Wiley.

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Table of Contents

1 Data Screening 1
2 One-Way Analysis of Variance Design 33
3 Estimation and Simultaneous Inference 73
4 Hierarchical or Nested Design 95
5 Two Crossed Factors: Fixed Effects and Equal Sample Sizes 117
6 Randomized Complete Block Design 143
7 Two Crossed Factors: Fixed Effects and Unequal Sample Sizes 163
8 Crossed Factors: Mixed Models 183
9 Repeated Measures Designs 203
10 Linear Regression: Fixed X Model 229
11 Linear Regression: Random X Model and Correlation 265
12 Multiple Regression 301
13 Multiple and Partial Correlation 331
14 Miscellaneous Topics in Regression 351
15 Analysis of Covariance 375
16 Summaries, Extensions, and Communication 403
App. A 409
App. B 425
Index 443
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