Study Design: Design of Surveys and Causal Studies

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.