https://github.com/newking9088/mitx_14.310x_data_analysis_for_social_scientist_fall_2020
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, 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. Students taking the graduate version will complete additional assignments. No prior preparation in probability and statistics is required, but familiarity with basic algebra and calculus is assumed.
https://github.com/newking9088/mitx_14.310x_data_analysis_for_social_scientist_fall_2020
Last synced: 28 days ago
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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, 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. Students taking the graduate version will complete additional assignments. No prior preparation in probability and statistics is required, but familiarity with basic algebra and calculus is assumed.
- Host: GitHub
- URL: https://github.com/newking9088/mitx_14.310x_data_analysis_for_social_scientist_fall_2020
- Owner: newking9088
- Created: 2020-11-16T19:28:26.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2020-11-16T19:49:25.000Z (over 4 years ago)
- Last Synced: 2025-04-01T13:37:58.629Z (about 2 months ago)
- Language: R
- Size: 72.4 MB
- Stars: 11
- Watchers: 1
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# MITx_14.310x_Data_Analysis_for_Social_Scientist_Fall_2020
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, 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. Students taking the graduate version will complete additional assignments. No prior preparation in probability and statistics is required, but familiarity with basic algebra and calculus is assumed.