Overview

The QSS curriculum is designed to cultivate rigorous analytical thinking, strong technical skills, and the ability to interpret and communicate quantitative findings within real-world social contexts. Students engage in interdisciplinary work that prepares them to evaluate evidence, design research, and apply data-driven methods to complex societal questions.

Individually and collectively, the program's courses are committed to the following learning outcomes:

Statistics: Students will understand and apply sampling theory, probability theory, linear regression, and measurement uncertainty and will be able to interpret and critique applications of statistical procedures as applied to randomized and observational data.

Mathematical modeling: Students will demonstrate knowledge of differential and integral calculus and introductory game-theoretic concepts.

Computing: Students will utilize key computational skills, including large-scale data analysis, natural language processing tasks, social network analysis, optimization techniques, and workflow skills.

The Program in Quantitative Social Science (QSS) brings together Dartmouth faculty and students who are interested in applying statistical, computational, and mathematical tools to social science questions. QSS offers undergraduates a minor and a major, both of which combine quantitative training with one or more of the social sciences. Through QSS, Dartmouth undergraduates can integrate the power of modern quantitative and computational methods with the substance of a social science discipline.