About This Course
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.
Why Take This Course?
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.
Learning Outcomes
- Intuition behind probability and statistical analysis.
- How to summarize and describe data.
- A basic understanding of various methods of evaluating social programs.
- How to present results in a compelling and truthful way.
- Skills and tools for using R for data analysis.
Instructors
Esther Duflo
Esther Duflo is the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics at MIT.
Sara Fisher Ellison
Sara Fisher Ellison is a Senior Lecturer in the MIT Economics Department. She was an undergraduate at Purdue University and received graduate degrees from both Cambridge University and MIT.
Requirements
No prior preparation in probability and statistics is required, but familiarity with algebra and calculus is assumed.
How To Join This Course
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