Econometrics for Data Science credit:

4 Hours

Builds a strong foundation in probability theory, statistical inference, regression analysis, and econometric methods for analyzing economic data. Reinforces theoretical concepts through assignments and an empirical research project using R so that students learn how to apply econometric techniques to analyze real-world data, derive meaningful insights, and present results professionally. Prerequisite: ECON 202 , ECON 203 , and ECON 471; or equivalent. Restricted to students in the MS in Economic Modeling, AI, and Data Science and MS in Economics and Computer Science programs. Exceptionally well-prepared students in the MS in Policy Economics program may enroll, but only with approval from the program directors.