Causal Inference (328-0-20)

Instructors

Laura Elizabeth Tipton

Meeting Info

Technological Institute M128: Tues, Thurs 12:30PM - 1:50PM

Overview of class

Introduction to modern statistical thinking about causal inference. Topics include completely randomized experiments, confounding, the potential outcomes framework, ignorability of assignment mechanisms, observational studies, matching, propensity scores, and other quasi-experimental designs.

Registration Requirements

STAT 320-2, STAT 350-0

Teaching Method

Combination of lecture and seminar.

Evaluation Method

Homework and projects.

Class Materials (Required)

We will use a combination of open source materials, including books and articles. The primary text will be: Gerber, A. S., & Green, D. P. (2012) Field Experiments: Design, Analysis, and Interpretation. WW Norton. Other sources will be available for free through the library or on the course system.

Class Attributes

Formal Studies Distro Area