Study Design: Design of Surveys and Causal Studies

Catalog description

Investigation of study designs collecting data and their implications for statistical inference. Design and analysis of surveys of populations, including stratification, clustering, multi-stage sampling, design-based inference, considerations when analyzing convenience samples and big data. Design and analysis of causal studies including randomized experiments, blocking, fractional factorial designs, non-randomized studies, propensity score analysis. Applications involving big data, health, policy, natural and social sciences. Not open to students who have taken Statistical Science 322. Recommended prerequisite: Statistical Science 210, 521L, or an equivalent course.