Data Analysis for

Social Scientists

Esther Dulfo & Sara Ellison - MIT

1. Introduction to Data Analysis for Social Scientists

2. Fundamentals to Probability

3. Random Variables, Distributions, and Joint Distributions

4. Gathering & Collecting Data

5. Summarising & Collecting Data

6. Joint, Marginal, and Conditional Probabilities

7. Foundations of Random Variables

8. Moments of Distribution

9. Expectation, Variance, & Introduction to Regression

10. Special Distributions

11. Special Distributions II: The Sample Mean, Central Limit Theorem, & Estimation

12. Assessing & Deriving Estimators

13. Confidence Intervals, Hypothesis Testing, & Power Calculations

14. Causality

15. Analysing Randomised Experiments 

16. More Explanatory Analysis: Nonparamatic Comparisons & Regressions

17. The Linear Model

18. The Multivariate Model

19. Practical Issues in Running Regressions

20. Omitted Variable Bias

21. Endogeneity & Instrument Variables

22. Experimental Design

23. Visualising Data