Course Information and Materials

Calendar & slides

Week Date Topic Slides
1 Tu 04/04 Introduction. Course Description (Syllabus etc). Review of background material.  Slides 1
  Th 04/06 Review of background material.   Slides 2
2 Tu 04/11 The multinomial and multivariate normal models (continuation). Large sample inference (Chapter 4).  Slides 2 & Slides 3
  Th 04/13 Hierarchical models (Chapter 5).  Slides 3 
3 Tu 04/18 Hierarchical models and meta-analysis (Chapter 5). Model checking (Chapter 6).   Slides 4
  Th 04/20  Model checking (Chapter 6). Model comparison (Chapter 7).   
4 Tu 04/25  TEST 1 (25%)   
  Th 04/27 

 Model comparison, model evaluation and expansion (Chapter 7).

  
5  Tu 05/02  Model comparison. Accounting for data collection schemes (Chapter 8).  
  Th 05/04  Accounting for data collection schemes: censoring and truncation (Chapter 8).   
6 Tu 05/09  Bayesian computation: Review and computationally efficient MCMC (Chapters 11, 12). 

Slides 5

Slides 6
  Th 05/11 Computationally efficient MCMC. Posterior Modes (Chapter 13).   Slides 7
7 Tu 05/16 MIDTERM (40%)   
  Th 05/18  Posterior Modes. Regression models (Chapter 14).   
8 Tu 05/23 Regression models (Chapter 14).  Slides 8 
  Th 05/25 Regression models (Chapter 14).    
9  Tu 05/30 G-priors, regularization and robust inference (Chapter 17).   
  Th 06/01 Mixture models (Chapter 22).  
10 Tu 06/06 TEST 2 (35%) Note: If this test has a take home part, this part will be given to you on Th 06/01 and will be due on Th 06/08.   
  Th 06/08 Mixture models (Chapter 22).