Multivariate Data Reduction and Discrimination with SAS Software

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9781580256964: Multivariate Data Reduction and Discrimination with SAS Software

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. The conceptual developments, theory, methods, and subsequent data analyses are presented 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 their 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. As the techniques discussed in this book also form the foundation of data mining methodology, the book will be of interest to data mining practitioners.

Supports releases 6.12 and higher of SAS software.

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About the Author:

Ravindra Khattree

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 graduate training 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, repeatd

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

Dayanand N. Naik is an associate professor of statistics at Old Doninion

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.

Review:

"...a core or supplementary text for graduate or senior undergraduate students, and a reference for researchers and practitioners." (SciTech Book News, Vol. 24, No. 4, December 2000)

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Book Description SAS Publishing, United States, 2000. Paperback. Book Condition: New. Language: English . Brand New Book ***** Print on Demand *****.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. Bookseller Inventory # AAV9781580256964

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Book Description SAS Publishing, United States, 2000. Paperback. Book Condition: New. Language: English . Brand New Book ***** Print on Demand *****. 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. Bookseller Inventory # AAV9781580256964

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