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Lecture 01: Introduction to 14.310x Data Analysis for Social Scientists
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Classroom Contents
Data Analysis for Social Scientists - Spring 2023
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- 1 Lecture 01: Introduction to 14.310x Data Analysis for Social Scientists
- 2 Lecture 02: Fundamentals of Probability
- 3 Lecture 03: Random Variables, Distributions, and Joint Distributions
- 4 Lecture 04: Gathering and Collecting Data
- 5 Lecture 05: Summarizing and Describing Data
- 6 Lecture 06: Joint, Marginal, and Conditional Distributions
- 7 Lecture 07: Functions of Random Variables
- 8 Lecture 08: Moments of Distribution
- 9 Lecture 09: Expectation, Variance, and Introduction to Regression
- 10 Lecture 10: Special Distributions
- 11 Lecture 11: Special Distributions, continued. The Sample Mean, Central Limit Theorem, and Estimation
- 12 Lecture 12: Assessing and Deriving Estimators
- 13 Lecture 13. Confidence Intervals, Hypothesis Testing, and Power Calculations
- 14 Lecture 14: Causality
- 15 Lecture 15: Analyzing Randomized Experiments
- 16 Lecture 16: (More) Explanatory Data Analysis: Nonparametric Comparisons and Regressions
- 17 Lecture 17: The Linear Model
- 18 Lecture 18: The Multivariate Model
- 19 Lecture 19: Practical Issues in Running Regressions
- 20 Lecture 20: Omitted Variable Bias
- 21 Lecture 21: Endogeneity and Instrument Variables
- 22 Lecture 22: Experimental Design
- 23 Lecture 23: Visualizing Data
