Beijing Institute of Mathematical Sciences and Applications

Further cultivate students' ability to employ probabilistic and statistical thinking and methods to analyze quantitative relationships among multiple variables in stochastic systems, and enhance their capacity to process random data. The content includes: multivariate normal distribution, analysis of variance, factor analysis, principal component analysis, discriminant analysis, cluster analysis, and other commonly used theories and methods in multivariate analysis. Through this course, students will master fundamental concepts, theories, and techniques in multivariate statistics, enabling them to analyze statistical problems involving multiple variables, comprehend variable interrelationships, and formulate appropriate models.