An Undergraduate Course in Causality

In the Fall quarter of 2024 we (a computer scientist and an economist as the faculty in charge of the course, with two economics graduate students as course assistants) taught an undergraduate course with the title “Causality, Decision Making, and Data Science,” cross-listed in the Economics Department, the Data Science Major, the Computer Science Department and the Graduate School of Business undergraduate program. The course was primarily intended for freshmen and sophomores, but because it was the first time we offered it, we also admitted juniors and a few seniors. We restricted enrollment to forty students to make the course interactive. The course was case-based, with minimal statistics requirements. It was successful from our perspective, and student evaluations reflected a similarly positive view. We would like to share here some of what we learned. The materials we put together, including an extensive set of slides, problem sets, and data sets, are available on this website <https://stanford-causalinference-class.github.io/> (https://stanford-causalinference-class.github.io/ <https://stanford-causalinference-class.github.io/> ).