Data Analysis in Social Science

Class 30
Practice 30
Independent work 90

Total 150

Course title

Lecture type

Elective

Course code

21-02-586

Semester

ECTS

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