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RECORD NUMBER: 3 OF 89

Main Title An introduction to multivariate statistical analysis
Author Anderson, T. W.
Publisher Wiley
Year Published 1958
OCLC Number 00180226
ISBN 0471026409; 9780471026402
Subjects Multivariate analysis ; Mathematics ; Mathematical statistics ; Multivariate analyse ; Statistiek ; Mathématiques ; Statistiques ; Analyse multivarie
Additional Subjects Multivariate analysis
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
EJEM  QA276.A6 1958 OCSPP Chemical Library/Washington,DC 03/05/2004
EKBM  QA276.A6 1958 Research Triangle Park Library/RTP, NC 08/31/2011
ELCM  QA276.A6 NVFEL Library/Ann Arbor, MI 01/01/1988
ESBM  QA276.A6 CPHEA/PESD Library/Corvallis,OR 09/13/2022
Collation xii, 374 pages illustrations 24 cm.
Notes
Includes bibliographical references (pages 352-368).
Contents Notes
The multivariate normal distribution -- Estimation of the mean vector and the covariance matrix -- The distributions and uses of sample correlation coefficients -- The generalized Tp2s-statistic -- Classification of observations -- The distribution of the sample covariance matrix and the sample generalized variance -- Testing the general linear hypotheses; analysis of variance -- Testing independence of sets of variates -- Testing hypotheses of equality of covariance matrices and equality of mean vectors and covariance matrices -- Principal components -- Canonical correlations and canonical variables -- The distribution of certain characteristic roots and vectors that do no depend on parameters -- A review of some other work in multivariate analysis -- Matrix theory. The multivariate normal distribution; Estimation of the mean vector and the covariance matrix; The distributions and uses of sample correlation coefficients; The generalized T2 statistic; Classification of observations; The distribution of the sample covariance matrix and the sample generalized variance; Testing the general linear hypothesis; analysis of variance; Testing independence of sets of variates; Testing hypotheses of equality of covariance matrices and equality of mean vectors and covariance matrices; Principal components; Canonical correlation and canonical variables; The distribution of certain characteristic roots and vectors that do not depend on parameters; A review of some other work in multivariate analysis.