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Data Analysis in Social Science

  • Class 30
  • Practice 30
  • Independent work 90
Total 150

Course title

Data Analysis in Social Science

Lecture type


Course code






Course overview

This master'ls level statistics and data analysis course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. It begins with essential notions of probability and statistics and proceeds to 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.

Minimal learning outcomes

  • Demonstrate understanding of reasoning logic in probability and statistical models
  • From selected use case, formulate summary and describe data sample
  • Demonstrate understanding of selected methods of evaluating social programs
  • From selected use case, demonstrate presenatation of results in a compelling and thruthful way
  • From selected tool/program language, demonstrate data analysis concepts and techniques

Preferred learning outcomes

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