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.