Introduction to Causal Inference

Lecture

Main Campus

Course Description

This course introduces the fundamental ideas and methods in causal inference, with examples drawn from education, economics, medicine, and digital marketing. Topics include potential outcomes, randomization, observational studies, matching, covariate adjustment, AIPW, heterogeneous treatment effects, instrumental variables, regression discontinuity, and synthetic controls.

STATS 209

Units: 3

See When It's Offered

Typically Offered

Not Available

Grading Basis

Letter or Credit/No Credit

Class Level

Graduate

Instructional Mode

In Person

Gen Ed Requirement(s)

None

Additional Information

Enrollment Requisites
Specific requirements or conditions that must be completed before or at the same time as you enroll.
Recommended Preparation
Courses, skills, or experiences that are suggested to help students succeed, but are not required for enrollment.
Rules
Specific policies or restrictions that apply to this course.

Introduction to Causal Inference

Course Description

Typically Offered

Grading Basis

Class Level

Instructional Mode

Gen Ed Requirement(s)

Additional Information

Enrollment Requisites

Antirequisite

Recommended Preparation

Prerequisite

Rules

Repeat Rules

Introduction to Causal Inference

Course Description

Typically Offered

Grading Basis

Class Level

Instructional Mode

Gen Ed Requirement(s)

Additional Information

Enrollment Requisites

Antirequisite

Recommended Preparation

Prerequisite

Rules

Repeat Rules