Bibliografía : p. 352-368.

1. Introduction -- 2. The multivariate normal distribution -- 3. Estimation of the mean vector and the covariance matrix -- 4. The distributions and uses of sample correlation coefficients -- 5. The generalized t2-statistic -- 6. Classification of observations -- 7. The distribution of the smaple covariance matrix and the sample generalized variance -- 8. Testing the general linear hypothesis: analysis of variance -- 9. Testing independence of sets variates -- 10. Testing hypotheses of quality of covariance matrices and equality of mean vectors and covariance matrices -- 11. Principal components -- 12. Canonical correlations and canonical variables -- 13. The distribution of certain characteristic roots and vectors that do not depend of parameters -- 14. A review of some other work in multivariate analysis -- Appendix: matrix theory.