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EPSY 5641: Causal Inference and Measurement for Data Science
Principles and practice of causal inference and measurement for data scientists. Topics include: fundamentals of causal inference, establishing causal (rather than correlational) relationships -- via AB tests, controlling for confounders, and the use of panel data -- and the fundamentals of measurement. Validity and reproducibility are themes throughout the course.
- Credits
- 2
- Offered
- Spring 2027, Fall 2026
- Campuses
- Storrs
- Requirements
- Open to students enrolled in the M.S. Data Science program or with instructor consent. Recommended preparation: Knowledge of Introductory inferential and descriptive statistics.
Spring 2027 sections
Taught by Kylie Anglin.
| Section | Type | Meets | Instructor | Campus | Room | Seats |
|---|---|---|---|---|---|---|
| 001 | LEC | TBA | Kylie Anglin | Storrs | Online | 42 of 50 open |
Seats as of Nov 12, 2026. HuskyScheduler shows live seats when you search.
Fall 2026 sections
Taught by Kylie Anglin.
| Section | Type | Meets | Instructor | Campus | Room | Seats |
|---|---|---|---|---|---|---|
| 001 | LEC | 3:35PM - 4:25PM / MoWe | Kylie Anglin | Storrs | ROWE 320 | 31 of 45 open |
Seats as of Nov 12, 2026. HuskyScheduler shows live seats when you search.
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