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Data Analysis for Social Scientists

Level: beginner
Esther Duflo

This statistics and data analysis course will introduce you to the essential notions of probability and statistics. We will cover techniques in modern data analysis: estimation, regression and econometrics, prediction, experimental design, randomized control trials (and A/B testing), machine learning, and data visualization. We will illustrate these concepts with applications drawn from real world examples and frontier research. Finally, we will provide instruction for how to use the statistical package R and opportunities for students to perform self-directed empirical analyses.

This course is designed for anyone who wants to learn how to work with data and communicate data-driven findings effectively, but it is challenging. Students who are uncomfortable with basic calculus and algebra might struggle with the pace of the class.

University: Massachusetts Institute of Technology
Platform: edX
Start: 05.02.2019
Recurrence: none
Language: English
Discipline: Economics, Social Sciences
Attendance: free
Certificate: 49.00 USD
Workload per week: 8.0 h
Tags data visualization , econometrics , estimation , experiments , forecast , machine learning , probability , randomized control trials , regression , statistics

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This project is brought to you by the Network for Pluralist Economics (Netzwerk Plurale Ökonomik e.V.).  It is committed to diversity and independence and is dependent on donations from people like you. Regular or one-off donations would be greatly appreciated.