An Introduction To Multivariate Statistical Analysis

An Introduction to Multivariate Statistical Analysis

1. Introduction; 2. The multivariate normal distribution; 3. Estimation of the mean vector and the covariance matrix; 4. Distributions and uses of sample correlation coefficients; 5. The generalized T2-Statistic; 6. Classification of observations; 7. The distribution of the sample covariance matrix and the sample generalized variance; 8. Testing the general linear hypothesis; Multivariate analysis of variance; 9. Testing independence of sets of variates; 10. Testing hypothesis of equality of coariance matrices and equality of mean vectors and covariance matrices; 11. Principal components; 12. Canonical correlations and canonical variables; 13. The distributions of characteristic roots and vectors; 14. Factor analysis.

An Introduction to Multivariate Statistical Analysis

An Introduction to Multivariate Statistical Analysis

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.