15.0341 Econometrics for Managers: Correlation and Causality in a Big Data World
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 be offered this semester (Fall 2018). It is instructed by J. Doyle.
Lecture occurs 2:30 PM to 4:00 PM on Tuesdays and Thursdays in E51-335.
This class counts for a total of 9 credits.
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