Using Multivariate Statistics

Linda S. Tabachnick, Barbara G.; Fidell,Linda S. Fidell

ISBN 10: 0060465719 / ISBN 13: 9780060465711

Published by Harpercollins College Div, Glenv, 1989

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Bibliographic Details

• Title: Using Multivariate Statistics
• Publisher: Harpercollins College Div, Glenv
• Publication Date: 1989
• Language: English
• ISBN 10: 0060465719
• ISBN 13: 9780060465711
• Binding: hardcover
• Edition: 2nd Edition
• Condition: Very Good

About this title

Synopsis

Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses through the most recent releases of SAS, SPSS, and SYSTAT, some not available in software manuals. The book maintains its practical approach, still focusing on the benefits and limitations of applications of a technique to a data set â when, why, and how to do it. Overall, it provides advanced students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics.

From the Back Cover

This book takes a practical approach to multivariate data analysis, with an introduction to the most commonly encountered statistical and multivariate techniques.

Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses through the most recent releases of SAS, SPSS, and SYSTAT, some not available in software manuals. The book maintains its practical approach, still focusing on the benefits and limitations of applications of a technique to a data set - when, why, and how to do it. Overall, it provides advanced users with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics.

For those interested in statistical analysis.