MS&E 125: Introduction to Applied Statistics

Instructor: Prof. Madeleine Udell Management Science and Engineering, Stanford University

Course description

An increasing amount of data is now generated in a variety of disciplines, ranging from finance and economics, to the natural and social sciences. Making use of this information requires both statistical tools and an understanding of how the substantive scientific questions should drive the analysis. In this hands-on course, we learn to explore and analyze real-world datasets. We cover techniques for summarizing and describing data, methods for statistical inference, and principles for effectively communicating results.

Class schedule

Lecture: MW 10:30-11:50am in Hewlett 201, starting March 30
Office hours: See calendar below for times and locations

All zoom links require SUID login for security.

Use office hours to discuss topics directly related to the course and also anything else that’s on your mind beyond the class: for example, questions about career trajectories, research opportunities in MS&E, and more.

Acknowledgements

The course materials — book, slides, homeworks, and quizzes — were developed using large language models, Claude in particular. The narrative conventions are mine: every chapter opens with a hook framing a consequential decision, every dataset is real and tied to a decision someone actually faces, and concepts arrive through examples and code before abstraction. AI produced first drafts and critiques within those conventions; my contribution was the curation — what to feed in, what to keep, and when to search for something better.

The course also draws inspiration from earlier MS&E 125 offerings and related courses developed by Sharad Goel, Mike Van Ness, Josh Grossman, Peter Frazier, and the Data 8 team.