15.0341 Econometrics for Managers: Correlation and Causality in a Big Data World


Class Info

Enables students to evaluate the quality of evidence supported by data, and to implement an empirical toolkit that provides credible answers to questions in finance, marketing, human resources, strategy, and general business planning. Reviews big-data tools designed to discover useful correlations. Introduces econometrics as a framework to go beyond correlations to causality, including an in-depth understanding of regression modelling including instrumental-variables estimation. Students apply these tools in classroom exercises, problem sets, and projects. Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details.

This class has no prerequisites.

15.0341 will not be offered this semester. It will be available in the Fall semester, and will be instructed by J. Doyle.

Lecture occurs 2:30 PM to 4:00 PM on Tuesdays and Thursdays in E51-149.

This class counts for a total of 9 credits.

You can find more information at the MIT + 15.0341 - Google Search site or on the 15.0341 Stellar site.

MIT 15.0341 Econometrics for Managers: Correlation and Causality in a Big Data World Related Textbooks
MIT 15.0341 Econometrics for Managers: Correlation and Causality in a Big Data World On The Web

© Copyright 2015