Brad DeLong : Cosma Shalizi: Advanced Data Analysis from an Elementary Point of View

 

Lectures:

  1. Regression: Predicting and Relating Quantitative Features
  2. The Truth About Linear Regression
  3. Model Evaluation: Error and Inference
  4. Smoothing Methods in Regression
  5. The Bootstrap
  6. Heteroskedasticity, Weighted Least Squares, and Variance Estimation
  7. Splines
  8. Additive Models
  9. Writing R Code
  10. Testing Regression Specifications
  11. Hypothesis Testing and Statistical Evidence
  12. Logistic Regression
  13. Generalized Linear Models and Generalized Additive Models
  14. GLM and GAM Examples
  15. Multivariate Distributions
  16. Density Estimation
  17. Simulation
  18. Relative Distributions and Smooth Tests
  19. Principal Components Analysis
  20. Factor Analysis
  21. Mixture Models
  22. Graphical Models
  23. Graphical Causal Models
  24. Identifying Causal Effects from Observations
  25. Estimating Causal Effects from Observations
  26. Time Series I, without latent variables
  27. Time Series II, with latent variables

Homework:

  1. What’s That Got to Do with the Price of Condos in California?
  2. Advantages of Backwardness
  3. How the Hyracotherium Got Its Mass
  4. It’s Not the Heat that Gets to You, It’s the Sustained Conjunction of Heat with Elevated Levels of Atmospheric Pollutants
  5. How the North American Mammalian Paleofauna Got a Crook in Its Curve
  6. What Makes the Union Strong?
  7. Fun with Density Estimation
  8. Red Brain, Blue Brain
  9. How the Recent Mammals Got Their Size Distribution
  10. Separated at Birth
  11. Brought to You by the Letters D, A, and G

Brad DeLong : Cosma Shalizi: Advanced Data Analysis from an Elementary Point of View

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