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Course14.310x23 lectures

Data Analysis for Social Scientists

Prof. Esther Duflo and Dr. Sara Ellison · Massachusetts Institute of Technology

Start with lecture 1 At MIT OpenCourseWare

About

This course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. We will start with essential notions of probability and statistics. We will proceed to cover techniques in modern data analysis: regression and econometrics, design of experiments, 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 on the use of the statistical package R, and opportunities for students to perform self-directed empirical analyses.

MITx Online

This course draws materials from 14.310x Data Analysis for Social Scientists, which is part of the MicroMasters Program in Data, Economics, and Design of Policy offered by MITx Online. The MITx Online course is entirely free to audit, though learners have the option to pay a fee, which is based on the learner’s ability to pay, to take the proctored exam and earn a course certificate. To access that course, create an MITx Online account and enroll in the course 14.310x Data Analysis for Social Scientists.

Lectures

Lecture Videos

  1. Lecture 01: Introduction to 14.310x Data Analysis for Social Scientists Video
  2. Lecture 02: Fundamentals of Probability Video
  3. Lecture 03: Random Variables, Distributions, and Joint Distributions Video
  4. Lecture 04: Gathering and Collecting Data Video
  5. Lecture 05: Summarizing and Describing Data Video
  6. Lecture 06: Joint, Marginal, and Conditional Distributions Video
  7. Lecture 07: Functions of Random Variables Video
  8. Lecture 08: Moments of Distribution Video
  9. Lecture 09: Expectation, Variance, and Introduction to Regression Video
  10. Lecture 10: Special Distributions Video
  11. Lecture 11: Special Distributions, continued. The Sample Mean, Central Limit Theorem, and Estimation Video
  12. Lecture 12: Assessing and Deriving Estimators Video
  13. Lecture 13. Confidence Intervals, Hypothesis Testing, and Power Calculations Video
  14. Lecture 14: Causality Video
  15. Lecture 15: Analyzing Randomized Experiments Video
  16. Lecture 16: (More) Explanatory Data Analysis: Nonparametric Comparisons and Regressions Video
  17. Lecture 17: The Linear Model Video
  18. Lecture 18: The Multivariate Model Video
  19. Lecture 19: Practical Issues in Running Regressions Video
  20. Lecture 20: Omitted Variable Bias Video
  21. Lecture 21: Endogeneity and Instrument Variables Video
  22. Lecture 22: Experimental Design Video
  23. Lecture 23: Visualizing Data Video

Syllabus and materials

At MIT OpenCourseWare, as the course publishes them.

Credits and licence

Institution
Massachusetts Institute of Technology
Department
Economics
Taught by
Prof. Esther Duflo, Dr. Sara Ellison
Term
Spring 2023
Level
Graduate
Language
English
Subjects
Mathematics, Economics, Society and politics
Source
MIT OpenCourseWare
Licence
CC BY-NC-SA 4.0, as MIT OpenCourseWare states it. Non-commercial use only. MIT OpenCourseWare's terms
Attribution
Prof. Esther Duflo, Dr. Sara Ellison. Data Analysis for Social Scientists. Spring 2023. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu/. License: Creative Commons BY-NC-SA.
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