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From the Back Cover
Real-world problems and data sets are the backbone of this groundbreaking book. Applied Multivariate Statistics with SAS® Software, Second Edition provides a unique approach to this topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information on
* mixed effects models
* applications of the MIXED procedure
* regression diagnostics with the correspoding IML procedure code
* covariance structures.
The authors' approach to the information aids professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding output accompany sample problems, and clear explanations of the various SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples. High-resolution graphs have been used in this new edition. --This text refers to an alternate Paperback edition.
About the Author
Ravindra Khattree, professor of applied statistics at Oakland University,
Rochester, Michigan, received his graduate training at the Indian Statistical
Institute in Calcutta.He received his Ph.D. at the University of Pittsburgh
in 1985. He is an author or coauthor of numerous research papers on
theoretical and applied statistics in various national and international
journals and conference proceedings. His research interests include
multivariate analysis, experimental designs, quality control, repeated
measures, and statistical inference. In addition to teaching graduate and
undergraduate courses, Dr. Khattree regularly consults with industry
and academic researchers on various applied statistics problems. He is also
an associate editor of Communications in Statistics and an editor of
InterStat, a statistics journal on the Internet.
Dayanand N. Naik
Dayanand N. Naik is an associate professor of statistics at Old Dominion
University, Norfolk, Virginia. He received his M.S. degree in statistics
from Karnatak University in Dharwad, India, and a Ph.D. degree in statistics
from the University of Pittsburgh in 1985. He has published his research in
several well-known journals, and he is the thesis advisor for many graduate
students. His research and teaching interests include multivariate analysis,
linear models, quality control, regression diagnostics, repeated measures
analysis, and growth curve models. Dr. Naik is also an editor of InterStat,
a statistics journal on the Internet.