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1. Overview
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2. Statistical Models
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3. Data Generation Processes
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4. Probability
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5. Theories of Inference
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6. Likelihood Inference
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7. Uncertainty Estimates
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8. Statistical Simulation
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9. Binary outcome models
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10. Interpreting and Presenting Statistical Results
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11. Discrete Outcome Models
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12. Model Evaluation
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13. Robust Standard Errors
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14. Research Design
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15. Model Dependence
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16. Matching Methods
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17. Multiple Equation Models
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18. Missing Data
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19. Anchoring Vignettes
Description:
First course for incoming Harvard Government Department PhD students; also taken by graduate and undergraduate students in other departments, and students elsewhere through the Harvard Extension School as Stat E-200. Instructor: Gary King.

Quantitative Social Science Methods

Harvard University
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#Social Sciences #Data Science #Data Analysis #Quantitative Research #Mathematics #Statistics & Probability #Probability #Statistical Models
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1. Overview