I.Contents：
1. Introduction of Multivariate Analysis
2. Matrix Algebra, Random Vectors, and Multivariate Normal
3. Statistical Inferences for Multivariate Distributions
4. Principal component Analysis
5. Factor Analysis
6. Discriminant Analysis
7. Cluster Analysis
8. Multivariate Analysis of Variance
9. Canonical Correlation Analysis
II.Course prerequisite：
III.Reference material ( textbook(s) )：
1. Flury, B. (1997) A First Course In Multivariate Statistics. Springer.
2. Srivastava, M. S. (2002) Methods of Multivariate Statistics. Wiley.
IV.Grading scheme：
Homework: 20%
Quiz: 20%
Midterm: 30%
Final: 30%