DSCI 609 Data Analytics for Social Sciences
This is a data analytics course specifically designed for students with strong interest in social and behavioral data analysis. Topics include sources of social and behavioral data, study designs and design of experiments for social and behavioral data, social and behavioral data management with SAS/R/Python/Stata, exploratory data analysis, multivariate analysis under the general regression framework, and causal inference. Depending on the instructor’s expertise and interest, usually half of the following topics will be covered at an introductory to intermediate level: classification, categorical data analysis, multivariate regression analysis, multilevel analysis, latent variable models (e.g., factor analysis and structural equation models), causal inference and propensity scoring, and social network analysis. Other newer topics can also replace some of these optional modeling topics.
Prerequisite recommended: DSCI 602 and SOC 686 or permission of the instructor.