MIT 14.310x Data Analysis for Social Scientists, Spring 2023
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16 learners
What you'll learn
This course includes
- 27.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 23 lessons • 27.5 hours of video
MIT 14.310x Data Analysis for Social Scientists, Spring 2023
23 lessons
• 27.5 hours
MIT 14.310x Data Analysis for Social Scientists, Spring 2023
23 lessons
• 27.5 hours
- Lecture 01: Introduction to 14.310x Data Analysis for Social Scientists 01:00:43
- Lecture 02: Fundamentals of Probability 01:07:55
- Lecture 03: Random Variables, Distributions, and Joint Distributions 01:12:09
- Lecture 04: Gathering and Collecting Data 01:23:54
- Lecture 05: Summarizing and Describing Data 01:08:46
- Lecture 06: Joint, Marginal, and Conditional Distributions 59:17
- Lecture 07: Functions of Random Variables 01:20:15
- Lecture 08: Moments of Distribution 01:18:52
- Lecture 09: Expectation, Variance, and Introduction to Regression 01:08:28
- Lecture 10: Special Distributions 01:15:28
- Lecture 11: Special Distributions, continued. The Sample Mean, Central Limit Theorem, and Estimation 01:13:44
- Lecture 12: Assessing and Deriving Estimators 01:06:54
- Lecture 13. Confidence Intervals, Hypothesis Testing, and Power Calculations 01:16:16
- Lecture 14: Causality 01:15:58
- Lecture 15: Analyzing Randomized Experiments 01:19:26
- Lecture 16: (More) Explanatory Data Analysis: Nonparametric Comparisons and Regressions 01:22:58
- Lecture 17: The Linear Model 01:20:25
- Lecture 18: The Multivariate Model 41:00
- Lecture 19: Practical Issues in Running Regressions 01:20:03
- Lecture 20: Omitted Variable Bias 01:20:25
- Lecture 21: Endogeneity and Instrument Variables 01:09:22
- Lecture 22: Experimental Design 01:10:39
- Lecture 23: Visualizing Data 01:22:02
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