Data Analysis for Social Scientists | Economics | MIT OpenCourseWare

Course Info

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Departments

Economics

As Taught In

Spring 2023

Level

Graduate

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Lecture Notes

Lecture 01: Introduction

Lecture 02: Fundamentals of Probability

Lecture 03: Random Variables, Distributions, and Joint Distributions

Lecture 04: Gathering and Collecting Data

Lecture 05: Summarizing and Describing Data

Lecture 06: Joint, Marginal, and Conditional Distributions

Lecture 07: Functions of Random Variables

Lecture 08: Moments of Distribution

Lecture 09: Expectation, Variance, and Introduction to Regression

Lecture 10: Special Distribution

Lecture 11: Special Distributions, continued. The Sample Mean, Central Limit Theorem, and Estimation

Lecture 12: Assessing and Deriving Estimators

Lecture 13. Confidence Intervals, Hypothesis Testing, and Power Calculations

Lecture 14: Causality

Lecture 15: Analyzing Randomized Experiments

Lecture 16: (More) Explanatory Data Analysis: Nonparametric Comparisons and Regressions

Lecture 17: The Linear Model

Lecture 18: The Multivariate Linear Model

Lecture 19: Practical Issues in Running Regressions

Lecture 20: Omitted Variable Bias

Lecture 21: Endogeneity and Instrument Variables

Lecture 22: Experimental Design

Course Info

Instructors

Departments

Economics

As Taught In

Spring 2023

Level

Graduate

Topics

Learning Resource Types

Lecture Notes

Lecture Videos

Podcasts

Problem Sets

Download Course

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