January 11, 2011

Advanced Data Analysis from an Elementary Point of View

At the intersection of Enigmas of Chance and Corrupting the Young.

2013

Course announcement and homepage

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. Simulation
  6. The Bootstrap
  7. Writing R Code
  8. Heteroskedasticity, Weighted Least Squares, and Variance Estimation
  9. Splines
  10. Additive Models
  11. Testing Regression Specifications
  12. Logistic Regression
  13. Generalized Linear and Generalized Additive Models
  14. Multivariate Distributions
  15. Density Estimation
  16. Relative Distributions and Smooth Tests
  17. Principal Components Analysis
  18. Factor Analysis
  19. Mixture Models
  20. Graphical Models
  21. Graphical Causal Models
  22. Identifying Causal Effects from Observations
  23. Estimating Causal Effects from Observations
  24. Discovering Causal Structure from Observations
  25. Time Series
Homework
  1. What's That Got to do with the Price of Condos in California?
  2. The Advantages of Backwardness
  3. An Insufficiently Random Walk Down Wall Street
  4. How the North American Mammalian Paleofauna Got a Crook in Its Regression Line
  5. It's Not the Heat that Gets to You, It's the Sustained Heat with Pollution
  6. How the Hyracotherium Got Its Mass
  7. Red Brain, Blue Brain
  8. How the Recent Mammals Got Their Size Distribution
  9. Cancelled
  10. Brought to You by the Letters D, A, and G
  11. Growth and Debt
    Exams:
  1. Nice Demo City, But Will It Scale?
  2. Choosing a Better History
  3. Final Exam
Self-Evaluation and Lessons Learned

2012

Course announcement and homepage.

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
Exams
  1. Diabetes
  2. Is This Test Really Necessary?
  3. Final Exam

Self-Assessment and Lessons Learned


2011

Course announcement.

Course homepage.

Lectures
  1. Regression: Predicting and Relating Quantitative Features
  2. The Truth About Linear Regression
  3. Evaluating Statistical Models
  4. Using Nonparametric Smoothing in Regression
  5. Moving Beyond Conditional Expectations: Weighted Least Squares, Heteroskedasticity, Variance Functions
  6. Density Estimation
  7. Simulation
  8. The Bootstrap
  9. Re-capitulation and Q&A, no notes
  10. Testing Regression Models
  11. Splines
  12. Additive Models
  13. More on hypothesis testing
  14. Logistic Regression and Logistic-Additive Models
  15. Generalized Linear Models and Generalized Additive Models
  16. GLM Practicals
  17. Principal Components Analysis
  18. Factor Analysis
  19. Mixture Models
  20. Mixture Model Examples and Complements
  21. Graphical Models
  22. Graphical Causal Models
  23. Estimating Causal Effects
  24. Discovering Causal Structure
  25. Conclusion: Statistical Data Analysis
Homeworks
  1. What's That Got to Do with the Price of Condos in California?
  2. The Advantages of Backwardness
  3. Old Heteroskedastic
  4. An Insufficiently Random Walk Down Wall Street
  5. Bootstrapping Will Continue Until Morale Improves
  6. Nice Demo City, But Will It Scale?
  7. Diabetes among the Pima
  8. Fair's Affairs
  9. Patterns of Exchange
  10. Estimating with DAGs
Exams
  1. Midterm: Urban Scaling, Continued
  2. Second exam: Mystery Multivariate Data
Other Handouts
Writing R Functions
Re-Writing Your Code

Self-Evaluation and Lessons Learned

Posted by crshalizi at January 11, 2011 10:30 | permanent link

Three-Toed Sloth:   Hosted, but not endorsed, by the Center for the Study of Complex Systems