1. Review multiple regression and univariate ANOVA week1
2. Introduction to matrix algebra week2
3. Introduction to multivariate analysis week2-3
   1. Multivariate normal distribution
   2. Variance-covariance matrix
   3. Sampling from multivariate normal population
   4. Tests for multivariate normality
4. Multivariate regression week4
   1. Least squares estimation
   2. ANOVA partitioning
   3. SCI
   4. Regression diagnostics
5. Multivariate analysis of experimental data week5-6
   1. One-way and two-way MANOVA
6. Analysis of repeated measures data week6-7
   1. Single and more than single populations
   2. The growth curve models
   3. Crossover designs
7. Discriminant analysis week9-10
   1. Basic concepts of classification
   2. classification into more than two groups
8. Principle component analysis week11-12
   1. Basic concepts of principal components analysis
   2. Use of principal components analysis in regression
9. Cluster analysis week13-14
   1. Initial analyses and distance measures
   2. Hierarchical clustering procedures
10. Canonical correlation analysis week15
    1. Canonical variates and correlations
    2. Interpreting the population canonical variables
11. Data mining

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