EC-752 Econometrics for Data Science
Dive into the analytical foundations of data-driven decision-making with Econometrics for Data Science, a rigorous yet accessible course tailored for Master’s students seeking to bridge statistical theory with real-world applications. This course provides a deep exploration of econometric techniques, including regression analysis, hypothesis testing, policy evaluation, instrumental variables, and panel data methods, all taught with a focus on practical implementation using R. By working with real-world datasets and mastering modern econometric tools, you will gain the skills to analyze complex problems across fields such as economics, finance, and public policy. Designed to enhance both your technical expertise and your ability to translate data insights into meaningful conclusions, this course is an essential elective for those aiming to excel in the evolving landscape of data science.