Course Description
Examines multivariate statistical techniques including exploratory factor analysis and principal components analysis, confirmatory factor analysis; moderation and mediation analysis; structural equation modeling and hierarchical linear modeling.
Syllabus
Student Learning Outcomes, Goals, Objectives:
Students successfully completing this course will be able to:
- Select and apply appropriate descriptive statistics to summarize and explore quantitative data.
- Explain the logic of sampling, probability, and statistical inference in hypothesis testing.
- Conduct and interpret foundational statistical tests to assess relationships between variables, including t-tests, ANOVA, correlations, and simple regression.
- Evaluate the quality of statistical evidence in published management research, identifying common errors in inference, effect size interpretation, and research design.
Course Grading Information:
| Activity/Performance Measure | Percentage/Points |
|---|---|
| Unit tests | 25% |
| Unit homework assignments | 25% |
| Capstone project | 25% |
| Oral examination | 25% |
Grading Scale:
| Percentage | Letter Grade |
|---|---|
| 94-100 | A |
| 90-93.99 | A- |
| 86-89.99 | B+ |
| 82-85.99 | B |
| 78-81.99 | B- |
| 70-77.99 | C |
| <70 | F |
Attendance/Participation:
The course is delivered in online, synchronous format. Attending synchronous class sessions is strongly encouraged, but not required. Attendance and participation are mandatory for the final examination, which will be conducted synchronously online at a time scheduled near the end of the semester.
Course Materials Purchased by the Students:
No course materials are required.
Scholarly Perspectives
This course engages diverse scholarly perspectives to develop critical thinking, analysis, and debate and inclusion of a reading does not imply endorsement.