An Introduction to Multivariate Statistical Analysis (Hardcover)

Theodore W. Anderson

ISBN 10: 0471360910 / ISBN 13: 9780471360919

Published by John Wiley & Sons Inc, New York, 2003

About this Item

Hardcover. Perfected over three editions and more than forty years, this field- and classroom-tested reference: * Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. * Treats all the basic and important topics in multivariate statistics. * Adds two new chapters, along with a number of new sections. * Provides the most methodical, up-to-date information on MV statistics available. Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780471360919

Bibliographic Details

Title: An Introduction to Multivariate Statistical ...

Publisher: John Wiley & Sons Inc, New York

Publication Date: 2003

Binding: Hardcover

Condition: new

Edition: 3rd Edition

About this title

Synopsis:

Perfected over three editions and more than forty years, this field- and classroom-tested reference:
* Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures.
* Treats all the basic and important topics in multivariate statistics.
* Adds two new chapters, along with a number of new sections.
* Provides the most methodical, up-to-date information on MV statistics available.

From the Back Cover:

A classic comprehensive sourcebook, now fully updated

For more than four decades An Introduction to Multivariate Statistical Analysis has been an invaluable text for students and a resource for professionals wishing to acquire a basic knowledge of multivariate statistical analysis. Since the previous edition, the field has grown significantly. This updated and improved Third Edition familiarizes readers with these new advances, elucidating several aspects that are particularly relevant to methodology and comprehension.

The Third Edition features new or more extensive coverage of:

• Patterns of Dependence and Graphical Models–a new chapter
• Measures of correlation and tests of independence
• Reduced rank regression, including the limited-information maximum-likelihood estimator of an equation in a simultaneous equations model
• Elliptically contoured distributions

Incorporation of the advice and comments of the readers of the first two editions as well as extensively classroom-tested techniques and calculations makes An Introduction to Multivariate Statistical Analysis, Third Edition, more valuable than ever for both professional statisticians and students of multivariate statistics.