Matrix algebra and random vectors
-random vectors
-distance
-sample geometry
-random sampling of sample mean vector and covariance matrix
-generalized variance
-matrix operations of sample values
Multivariate normal distribution
-density and properties
-sampling from multivariate normal and MLE
-sampling distribution and large sample behavior of X and S
-assessing the assumption of normality
-transformation to near normality
Inferences about a mean vector
-inference for a normal population mean
-Hotelling's T2 and likelihood ratio test
-confidence regions and simultaneous comparisons of component means
-large sample inferences about a population mean vector
Comparisons of several multivariate means
-paired comparisons and repeated measures design
-comparing mean vectors from two populations
-comparing several multivariate population means (one-way MANOVA)
Discrimination and classification (2/2)
-evaluation of classification functions
-classification with several populations
-fisher's method for discriminating among several populations
