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Detalles bibliogr�ficos

T�tulo: Multivariate Data Reduction and Discrimination with SAS Software
Editor: SAS Institute
Fecha de publicaci�n: 2000
Idioma: Ingl�s
ISBN 10: 1580256961
ISBN 13: 9781580256964
Encuadernaci�n: paperback
Edici�n: 2nd Edition.
Estado: Good

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Sinopsis

Multivariate data commonly encountered in a variety of disciplines is easy to understand with the approaches and methods described in Multivariate Data Reduction and Discrimination with SAS Software. Authors Ravindra Khattree and Dayanand Naik present the conceptual developments, theory, methods, and subsequent data analyses systematically and in an integrated manner. The data analysis is performed using many multivariate analysis components available in SAS software. Illustrations are provided using an ample number of real data sets drawn from a variety of fields, and special care is taken to explain the SAS codes and the interpretation of corresponding outputs. As a companion volume to the authors' previous book, Applied Multivariate Analysis with SAS Software, which discusses multivariate normality-based analyses, this book covers topics where, for the most part, assuming multivariate normality (or any other distributional assumption) is not crucial. Since the techniques discussed in this book also form the foundation of data mining methodology, the book will be of interest to data mining practitioners.

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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 Pittsburg 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 statistic problems. He is also an associate editor of Communications in Statistics and an editor of InterStat , a statistics journal on the Internet. Additionally, Dr. Khattree is coauthor, with Dr. Naik, of Applied Multivariate Statistics with SAS Software, Second Edition.

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 on 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. Additionally, Dr. Naik is coauthor, with Dr. Khattree, of Applied Multivariate Statistics with SAS Software, Second Edition.

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