MIT 14.310x Data Analysis for Social Scientists, Spring 2023 (English)

   Thursday, November 28, 2024   

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Lecture 1: Lecture 01: Introduction to 14.310x Data Analysis for Social Scientists

Lecture 2: Lecture 02: Fundamentals of Probability

Lecture 3: Lecture 03: Random Variables, Distributions, and Joint Distributions

Lecture 4: Lecture 04: Gathering and Collecting Data

Lecture 5: Lecture 05: Summarizing and Describing Data

Lecture 6: Lecture 06: Joint, Marginal, and Conditional Distributions

Lecture 7: Lecture 07: Functions of Random Variables

Lecture 8: Lecture 08: Moments of Distribution

Lecture 9: Lecture 09: Expectation, Variance, and Introduction to Regression

Lecture 10: Lecture 10: Special Distributions

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

Lecture 12: Lecture 12: Assessing and Deriving Estimators

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

Lecture 14: Lecture 14: Causality

Lecture 15: Lecture 15: Analyzing Randomized Experiments

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

Lecture 17: Lecture 17: The Linear Model

Lecture 18: Lecture 18: The Multivariate Model

Lecture 19: Lecture 19: Practical Issues in Running Regressions

Lecture 20: Lecture 20: Omitted Variable Bias

Lecture 21: Lecture 21: Endogeneity and Instrument Variables

Lecture 22: Lecture 22: Experimental Design

Lecture 23: Lecture 23: Visualizing Data