Data Science for Economic and Social Issues

Catalog description

Credits 3. 3 Lecture Hours. Application of economic and quantitative methods to the analysis of decisions made by individuals, firms and policymakers; focuses on causal inference and the identification strategies that distinguish correlation from causation; includes coding fundamentals and data management techniques to clean, summarize and analyze data using statistical software; develops skills in implementing and interpreting empirical models, presenting results through data visualization and written analysis and evaluating the effectiveness of policies and programs; topics and applications vary across instructors. May be taken two times for credit as content varies. Prerequisites: Grade of C or better in ECMT 463 or ECMT 464 , or approval of instructor.