| |
Feb 18, 2026
|
|
|
|
|
STAT 52400 - Applied Multivariate Analysis
Credit Hours: 3.00. Extension of univariate tests in normal populations to the multivariate case, equality of covariance matrices, multivariate analysis of variance, discriminant analysis and misclassification errors, canonical correlation, principal components, factor analysis. Strong emphasis will be placed on use of existing computer programs.
Learning Outcomes
1. Describe the underlying mathematical formulation associated with multivariate techniques such as principal components, factor analysis, discrimination and classification, and clustering.
2. Derive properties associated with the multivariate normal probability distribution.
3. Analyze data using multivariate techniques such as principal components, factor analysis, discrimination and classification, and clustering.
4. Use appropriate software, such as R, to describe, visualize, and analyze multivariate data.
5. Communicate the results of the work to a variety of audiences, including a non-statistician.
Credits: 3.00
Add to Portfolio (opens a new window)
|
|
