1. Multivariate normal distribution.
2. Wishart and Hotelling distribution.
3. Multivariate statistical inference.
4. Principal components and factor analysis.
5. Canonical correlations, correspondence analysis.
6. Discriminant and cluster analysis.
7. Projections-based methods, data depth.
8. Statistical software.
An introduction to traditional and modern methods of multivariate statistics.