Course Description
Multivariate normal distribution. Cluster analysis, discriminant analysis, canonical correlation, principal component analysis, factor analysis, multivariate analysis of variance. Use and interpretation of relevant statistical software. Prerequisite: ERM 680 and ERM 681, or STA 573, or STA 662, or permission of instructor.
Syllabus
Student Learning Outcomes, Goals, Objectives:
Students successfully completing this course will be able to:
- Explain the purpose of multivariate analysis.
- Describe the relevant statistical theories (e.g., assumptions, limitations).
- Use statistical software to conduct multivariate analysis.
- Interpret results.
Course Grading Information:
| Activity/Performance Measure | Percentage/Points |
|---|---|
| Assignment — Four homework assignments | 70% |
| Quizzes — Four quizzes | 30% |
Attendance/Participation:
Attendance/participation is not a graded component included in the student's final grade for this course.
Course Materials Purchased by the Students:
Applied Multivariate Statistical Analysis — Johnson, R. A. & Wichern, D. W., Pearson, 2023, ISBN 9780134995397
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate and inclusion of a reading does not imply endorsement.