Schedule
Below is the schedule for the semester. You should:
- complete readings before class;
- submit answers to warmup questions on Canvas by 1 hour before class; and
- turn in homework assignments, printed and in-person to your TF/CA, by the beginning of class.
The readings refer to following texts:
- ROS: Regression and Other Stories by Andrew Gelman, Jennifer Hill, & Aki Vehtari
- TE: The Effect: An Introduction to Research Design and Causality by Nick Huntington-Klein
ImportantThis schedule is subject to change
Ideally, we will be able to cover all of this content in the semester, but given that there may be unforeseen issues (e.g., university closures or sickness) this schedule is subject to change. However, if there are changes this page will be updated and there will be an announcement made on Ed Discussion Board.
| Date | Title | Reading |
|---|---|---|
| Module 1: An introduction to ‘quantitative social science’ | ||
| 9/2/2026 | First Class | None |
| 9/9/2026 | Second Class | ROS Ch 1; TE Chs 0 & 1 |
| Module 2: Critical thinking: the role of prediction and defining research questions | ||
| 9/14/2026 | First Class | ROS Apps A.1-A.3 |
| 9/16/2026 | Second Class | TE Ch 2 |
| Module 3: Back to the basics: data collection, description, and visualization | ||
| 9/21/2026 | First Class | ROS Ch 2 |
| 9/23/2026 | Second Class | TE Chs 3 & 4 |
| Module 4: Nuts and bolts: a review of some math and probability | ||
| 9/28/2026 | First Class | ROS Ch 3 |
| 9/30/2026 | Second Class | ROS Apps A.4-A.5 |
| Module 5: Bread and butter: statistical inference and identification | ||
| 10/5/2026 | First Class | ROS Ch 4 |
| 10/7/2026 | Second Class | TE Ch 5 |
| Module 6: The city on the hill: simulation(s) and causal diagrams | ||
| 10/14/2026 | First Class | ROS Ch 5 & Apps A.6-A.7 |
| 10/19/2026 | Second Class | TE Chs 6 & 7 |
| Module 7: Laying the foundation: background on regression and ‘doors’ in causal inference | ||
| 10/21/2026 | First Class | ROS Ch 6 |
| 10/26/2026 | Second Class | TE Chs 8 & 9 |
| Module 8: y = mx + b: regression with a single predictor and causal treatment effects | ||
| 10/28/2026 | First Class | ROS Ch 7 |
| 11/2/2026 | Second Class | TE Ch 10 |
| Module 9: y = b1x1 + b2x2 + b3x3…: linear regression with multiple predictors | ||
| 11/4/2026 | First Class | ROS Ch 10 |
| 11/9/2026 | Second Class | TE Chs 11 & 12 |
| Module 10: But what about causality?: experiments and selection on observables | ||
| 11/11/2026 | First Class | ROS Ch 18 |
| 11/16/2026 | Second Class | ROS Secs 20.1-20.3; TE Secs 13.1, 13.2.0-13.2.1, 13.4.1-13.4.3 |
| Module 11: Rubber meets the road: using regression for experiments and matching | ||
| 11/18/2026 | First Class | ROS Ch 19 |
| 11/23/2026 | Second Class | ROS Secs 20.4, 20.5, & 20.7; TE Secs 14.1-14.3, 14.5, & 14.6 |
| Module 12: All by design: design-based causal inference | ||
| 11/30/2026 | First Class | TE 18.1; Card & Krueger (1994) |
| 12/2/2026 | Second Class | TE 20.1; Hoekstra (2009) |
| Reading and Finals Weeks | ||
| 12/2/2026 | Practice exam distributed | |
| Exam Week (TBD) | Final exam | |