
Applied Multivariate Statistics With SAS Software, 2e + Multivariate Data Reduction and Discrimination with SAS Software Set
Wiley (Publisher)
Will be published approx. on 29. February 2008
Book
Paperback/Softback
944 pages
978-0-470-38805-1 (ISBN)
Description
This set contains 9780471322993 Applied Multivariate Statistics with SAS? Software, 2nd Edition and 9780471323006 Multivariate Data Reduction and Discrimination with SAS? Software both by Ravindra Khattree and Dayanand N. Naik.
More details
Edition
Revised edition
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 280 mm
Width: 218 mm
Thickness: 17 mm
Weight
1996 gr
ISBN-13
978-0-470-38805-1 (9780470388051)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Ravindra Khattree is an Indian-American statistician and professor of statistics at Oakland University. His contribution to the Fountain-Khattree-Peddada Theorem in Pitman measure of closeness is one of the important results of his work. Khattree is the coauthor of two books and has coedited two volumes. Dayanand N. Naik is the author of Applied Multivariate Statistics With SAS Software, Second Edition + Multivariate Data Reduction and Discrimination with SAS Software Set, published by Wiley.
Content
Multivariate Analysis Concepts.
Graphical Representation of Multivariate Data.
Multivariate Regression.
Multivariate Analysis of Experimental Data.
Analysis of Repeated Measures Data.
Analysis of Repeated Measures Using Mixed Models.
References.
Appendices.
Index.
TOC for Software:
Basic Concepts for Multivariate Statistics.
Principal Component Analysis.
Canonical Correlation Analysis.
Factor Analysis.
Discriminant Analysis.
Cluster Analysis.
Correspondence Analysis.
Appendix.
References.
Index.
Graphical Representation of Multivariate Data.
Multivariate Regression.
Multivariate Analysis of Experimental Data.
Analysis of Repeated Measures Data.
Analysis of Repeated Measures Using Mixed Models.
References.
Appendices.
Index.
TOC for Software:
Basic Concepts for Multivariate Statistics.
Principal Component Analysis.
Canonical Correlation Analysis.
Factor Analysis.
Discriminant Analysis.
Cluster Analysis.
Correspondence Analysis.
Appendix.
References.
Index.