Overview

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.

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 principles drawn from sampling theory and probability theory; estimate and interpret linear regressions; incorporate measures of uncertainty in statistical exercises; and interpret and critique applications of statistical procedures applied to both randomized and observational data.

Mathematical modeling: students will demonstrate knowledge of differential and integral calculus and basic optimization techniques.

Computing: students will apply key computational principles in the areas of large-scale data analysis, natural language processing, social network analysis, and reproducible workflow development.