Calendar
Assignments
Assignment due dates will be visible in BruinLearn and Gradescope. They follow a pattern:
- M 5pm: Post-lecture quiz due
- W 5pm: Post-lecture quiz due
- F 5pm: Problem set due
Lecture topics
Below is a tentative plan for the dates each topic will be covered. If you are absent, you can review the corresponding course page to learn the material.
| Date | Website Page |
|---|---|
| 1/5 | Research Questions in Social Data Science |
| Software Prerequisites | |
| Basics of R | |
| 1/7 | Visualizing a Distribution |
| Summary Statistics | |
| 1/12 | Population Sampling |
| 1/14 | Confidence Intervals |
| 1/19 | No class: Martin Luther King, Jr. Day |
| Models for Subgroup Summaries | |
| 1/21 | Linear Regression |
| 1/26 | Logistic Regression |
| 1/28 | Forests |
| 2/2 | Data-Driven Estimator Selection |
| 2/4 | Are Complex Models Better? |
| Causal Inference under Measured Confounding | |
| 2/9 | Defining Causal Effects |
| 2/11 | Exchangeability |
| 2/16 | No class: Presidents’ Day |
| 2/18 | Directed Acyclic Graphs |
| 2/23 | Matching |
| 2/25 | Models for Causal Inference |
| Causal Inference with Unmeasured Confounding | |
| 3/2 | Difference in Difference |
| 3/4 | Regression Discontinuity |
| 3/9 | Instrumental Variables |
| 3/11 | Course Recap |