Data Science 241

Experiments and Causal Inference

3 units

Course Description

This course introduces students to experimentation in the social sciences. This topic has increased considerably in importance since 1995, as researchers have learned to think creatively about how to generate data in more scientific ways, and developments in information technology have facilitated the development of better data gathering. Key to this area of inquiry is the insight that correlation does not necessarily imply causality. In this course, we learn how to use experiments to establish causal effects and how to be appropriately skeptical of findings from observational data.

Skill Sets

Experimental design / Statistical analysis / Communicating results / Cleaning data / Mining and exploring data



Current Course Designers

Profile profile for

D. Alex Hughes
D. Alex Hughes
Assistant Adjunct Professor
305B South Hall

Original Course Designers

Previously listed as DATASCI W241.


Data Science 201 and 203. MIDS students only.

Requirements Satisfied

Applied Data Science Certificate — Elective

Last updated:

October 6, 2022