ST 553: Multivariate Regression Analysis

ST 553: Multivariate Regression Analysis#

Methods and business applications of multivariate analysis, discriminant analysis, canonical correlation, factor analysis, cluster analysis, and principal components.

  • Background

    • Matrix Algebra and Random Vectors

    • Sample Geometry and Random Sampling

    • Multivariate Normal Distribution

  • Multivariate Inference

    • Inferences About a Mean Vector

    • Comparisons of Several Multivariate Means

  • Multivariate Linear Models

    • Multivariate Linear Regression

    • Regression Trees*

    • Experimental Design

  • Unsupervised Learning

    • Principal Components

    • Factor Analysis

    • Canonical Correlation*

    • Clustering

  • Supervised Learning

    • Discrimination

    • Classification

The notes in this section are based on the in-class materials provided for this course.