Schedule
The order of topics may change based on students' interests and the class's pace. If changes are made, I will announce them at least one week in advance, so students have time to prepare the readings for the upcoming classes.
Please review the materials before attending each meeting.
Date | # | Topics | Slides | Materials | Code | Data | Assignments |
---|---|---|---|---|---|---|---|
Aug 22 | 01 | Introduction & Python Crash Course |
Data Merging & OLS
Logistic Regression |
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Aug 29 | 02 | Randomized Trials | Cohen's D | ||||
Sep 05 | 03 | Instrumental Variables | |||||
Sep 12 | 04 | Regression Discontinuity | Quiz 1 | ||||
Sep 19 | Wellness Week: No Class | ||||||
Oct 03 | 05 | DiD 1: Introduction to Diff-in-Diff | |||||
Oct 10 | 06 | DiD 2: Synthetic Control | PS 1 | ||||
Oct 17 | 07 | DiD 3: Time Variant Treatments | |||||
Oct 17 | 08 | ML 1: Introduction to Machine Learning | |||||
Oct 24 | 09 | ML 2: Supervised ML - Classification | |||||
Oct 31 | 10 | ML 3: Supervised ML - Regression | Quiz 2 | ||||
Nov 07 | 11 | Factor Analysis (Guest Lecture by William Swann) | |||||
Nov 14 | 12 | ML 4: Unsupervised ML - Clustering | PS 2 | ||||
Nov 14 | Common Method Bias (Guest Lecture by William Swann) | ||||||
Nov 21 | 13 | ML 5: Basics of Natural Language Processing | |||||
Nov 28 | Thanksgiving | ||||||
Dec 05 | Final Project Presentations |
PS 3
FP |