9780471881049-047188104X-Multivariate Observations (Wiley Series in Probability and Statistics)

Multivariate Observations (Wiley Series in Probability and Statistics)

ISBN-13: 9780471881049
ISBN-10: 047188104X
Edition: 1
Author: George A.F. Seber
Publication date: 1984
Publisher: Wiley
Format: Hardcover 712 pages
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Book details

ISBN-13: 9780471881049
ISBN-10: 047188104X
Edition: 1
Author: George A.F. Seber
Publication date: 1984
Publisher: Wiley
Format: Hardcover 712 pages

Summary

Multivariate Observations (Wiley Series in Probability and Statistics) (ISBN-13: 9780471881049 and ISBN-10: 047188104X), written by authors George A.F. Seber, was published by Wiley in 1984. With an overall rating of 4.2 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Multivariate Observations (Wiley Series in Probability and Statistics) (Hardcover) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

WILEY-INTERSCIENCE PAPERBACK SERIES

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

"In recent years many monographs have been published on specialized aspects of multivariate data-analysis–on cluster analysis, multidimensional scaling, correspondence analysis, developments of discriminant analysis, graphical methods, classification, and so on. This book is an attempt to review these newer methods together with the classical theory. . . . This one merits two cheers."
–J. C. Gower, Department of Statistics
Rothamsted Experimental Station, Harpenden, U.K.
Review in Biometrics, June 1987

Multivariate Observations is a comprehensive sourcebook that treats data-oriented techniques as well as classical methods. Emphasis is on principles rather than mathematical detail, and coverage ranges from the practical problems of graphically representing high-dimensional data to the theoretical problems relating to matrices of random variables. Each chapter serves as a self-contained survey of a specific topic. The book includes many numerical examples and over 1,100 references.

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