Schedule
Weekly Schedule (2026)
| Week | Date (Wed) | Content | Lab | Main Readings |
|---|---|---|---|---|
| w1 | 25 Feb | How to ask a question in psychological science? | Git and GitHub | — |
| w2 | 4 Mar | Causal diagrams: elementary structures | Install R and RStudio | H&R Ch 1–2 |
| w3 | 11 Mar | Causal diagrams: confounding bias | Regression, graphing, and simulation | H&R Ch 3, 6 |
| w4 | 18 Mar | Interaction, measurement bias, selection bias | Regression and confounding bias | H&R Ch 5, 7–8 |
| w5 | 25 Mar | Causal inference: average treatment effects | Average treatment effects | H&R Ch 1–3 (review) |
| w6 | 2 Apr | Effect modification / CATE | CATE and effect modification | H&R Ch 4 |
| — | 8 Apr | Mid-trimester break | — | — |
| — | 15 Apr | Mid-trimester break | — | — |
| w7 | 22 Apr | In-class test 1 (20%) | — | — |
| w8 | 29 Apr | Heterogeneous treatment effects and machine learning | RATE and QINI curves | — |
| w9 | 6 May | Resource allocation and policy trees | Policy trees | — |
| w10 | 13 May | Classical measurement theory from a causal perspective | Measurement invariance | H&R Ch 9 |
| w11 | 20 May | In-class test 2 (20%) | — | — |
| w12 | 27 May | Student presentations (10%) | — | — |
Labs run in the final 60–90 minutes of the seminar. Nine labs across weeks 1–6 and 8–10. Your best eight lab diaries count toward the 10% assessment. See Assessments for due dates.