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Methods of multivariate analysis / Alvin C. Rencer and William F. Christensen

By: Contributor(s): Material type: TextTextPublication details: New Jersey : John Wiley & Son, Inc., c2012Edition: Third EditionDescription: xxv, 758 pages : illustrations ; 24 cmISBN:
  • 9780470178966
Subject(s): LOC classification:
  • QA 278 .R46 2012
Contents:
1. Introduction -- 2. Matrix algebra -- 3. Characterizing and displaying multivariate data -- 4. The Multivariate normal distribution -- 6. Multivariate analysis of variance -- 7. Tests on covariance matrices -- 8. Discriminant analysis : description of group separation -- 9. Classification analysis : allocation of observations of groups -- 10. Multivariate regression -- 11. Canonical correlation -- 12. Principal component analysis -- 13. Exploratory factor analysis -- 15. Cluster analysis -- 16. Graphical procedures.
Summary: This new edition, now with a co-author, offers a complete and up-to-date examination of the field. The authors have streamlined previously tedious topics, such as multivariate regression and MANOVA techniques, to add newer, more timely content.
Item type: Books
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Holdings
Item type Current library Home library Collection Call number Copy number Status Date due Barcode
Books Books National University - Manila LRC - Graduate Studies General Circulation Gen. Ed - CEAS GC QA 278 .R46 2012 (Browse shelf(Opens below)) c.1 Available NULIB000014116

Includes bibliographical references and index.

1. Introduction -- 2. Matrix algebra -- 3. Characterizing and displaying multivariate data -- 4. The Multivariate normal distribution -- 6. Multivariate analysis of variance -- 7. Tests on covariance matrices -- 8. Discriminant analysis : description of group separation -- 9. Classification analysis : allocation of observations of groups -- 10. Multivariate regression -- 11. Canonical correlation -- 12. Principal component analysis -- 13. Exploratory factor analysis -- 15. Cluster analysis -- 16. Graphical procedures.

This new edition, now with a co-author, offers a complete and up-to-date examination of the field. The authors have streamlined previously tedious topics, such as multivariate regression and MANOVA techniques, to add newer, more timely content.

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