Multivariate Statistical Analysis (DATA 130044)

Lecture Time and Venue:

Grading:

Reading Materials:

• Richard A. Johnson, Dean W. Wichern. "Applied Multivariate Statistical Analysis". Pearson; 6th Edition. [link]
• Theodore W. Anderson. "An Introduction to Multivariate Statistical Analysis". John Wiley & Sons Inc; 3rd Edition. [link]
• 张尧庭/方开泰. "多元统计分析引论". 科学出版社, 2015. [link]

Courseware (subject to changes):

• Sep 04: Introdution, Review of Linear Algebra and Optimization. [pdf]
• Sep 11: Random Vectors and Matrices, Random Samples, Generalized Variance. [pdf]
• Sep 18: Multivariate Normal Distribution, Linear Transformation, Marginal Distribution. [pdf]
• Sep 25: Singular Normal Distribution, Conditional Distribution. [pdf]
• Oct 09: Characteristic Function, Maximum Likelihood Estimator of Mean and Covariance. [pdf]
• Oct 16: Maximum Likelihood Estimator, Distribution Theory. [pdf]
• Oct 23: Unbiasedness, Sufficiency, Completeness, Efficiency. [pdf]
• Oct 30: Consistency, Asymptotic Normality, Bayesian Estimation. [pdf]
• Nov 06: James–Stein Estimator, Noncentral Chi-Squared Distribution. [pdf]
• Nov 13: Hypothesis Testing for the Mean (Covariance is Known), Sample Correlation Coefficient. [pdf]
• Nov 20: The Asymptotic Distribution of Sample Correlation, The Likelihood Ratio Criterion, The Wishart Distribution. [pdf]
• Nov 27: The Density of Wishart Distribution, T²-Statistic and F-Distribution, The Inverted Wishart Distribution. [pdf]
• Dec 04: The Characteristic Function of Wishart Distribution, More Matirx Variate Distributions, Revisiting Likelihood Ratio Criterion. [pdf]
• Dec 11: Multivariate Analysis of Variance, (Bayesian) Multivariate Linear Regression. [pdf]
• Dec 18: (Kernel, Probabilistic) Principal Component Analysis, Factor Analysis, Course Summary. [pdf]