Course Introduction
This advanced course covers multivariate statistical techniques for analyzing complex datasets with multiple variables, including dimension reduction, classification, and modeling approaches.
Course Content
- Week 1: Multivariate Data Exploration
- Week 2: Principal Component Analysis
- Week 3: Factor Analysis
- Week 4: Cluster Analysis
- Week 5: Discriminant Analysis
- Week 6: MANOVA
- Week 7: Canonical Correlation
- Week 8: Multidimensional Scaling
Assignments
Assignment 1: PCA Implementation
Perform PCA on a high-dimensional dataset and interpret components.
Download DatasetAssignment 2: Market Segmentation
Use clustering techniques to segment customer data.
Download DatasetAssignment 3: MANOVA Analysis
Analyze experimental data with multiple dependent variables.
Download DatasetCase Studies
Genomic Data Analysis
Apply dimension reduction techniques to high-dimensional genomic data.
Consumer Behavior Segmentation
Use multivariate techniques to identify consumer segments.
Datasets
Recommended Textbooks
- "Applied Multivariate Statistical Analysis" by Johnson & Wichern
- "Multivariate Data Analysis" by Hair et al.
- "An Introduction to Applied Multivariate Analysis" by Everitt & Hothorn