• Course slides of Christian Robert. Based on his book. 
• Bayesian Statistics course. By Francesca Dominici.
• Bayesian Statistics for Biologists. By Bob O'Hara.
  
• Bayesian Inference and Decision Theory.  By Kathryn Laskey.  Lots of material on graphical models, numerical methods and decision analysis.
• An article on Bayesian statistics by José Bernardo. 

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• Introduction: statistical inference

• The likelihood principle from Wikipedia.
  
• Fiducial inference. A 1978 article by J.G. Pedersen from International Statistical Review, 46, 147-170..  
• Objections to Bayesian statistics (with comments). From the online journal, Bayesian Analysis (2008).

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• Conjugate families of distributions

• Basics of exponential families and Bayesian inference. Course slides by Tom Mitchell.
  

 
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• The normal distribution

• Two interesting powerpoint classes on inference for the normal distribution.  Class 1 and Class 2
  

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• The prior distribution

• An introduction to prior elicitation.  By Baddeley et al.
  
• A catalogue of noninformative prior distributions.  A fairly definitive list. 
• Problems with noninformative priors. Points out some of the logical inconsistencies. 
• Introduction to objective Bayesian statistics.  Course slides by Jose Bernardo.
  
• Bayesian reference analysis.  Notes from the doctoral course of Jose Bernardo.

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• Estimation and hypothesis tests

• Bayes factors from the Wikipedia.
  
• Bayesian hypothesis testing and Bayes factors. Powerpoint slides.
• An article by Siva  Sivaganesan in the ISBA bulletin for December 2002 with some useful references. 

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• Large samples

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• Regression and linear models

• A powerpoint presentation on Bayesian regression. (.ppt format)
• Some nice slides on Bayesian regression. (.pdf format)

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• Hierarchical models

• De Finettis Theorem. From the Wikipedia.
• Empirical Bayes. Course notes in Word (.doc format)
  
• Modelos jerárquicos. Apuntes en español de Eduardo Gutierrez Peña.
• A short course on hierarchical models. Notes written by David Draper based on his book. (.ps format)

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• Numerical methods I

• Métodos computacionales en español de Eduardo Gutierrez Peña.  Incluye también materia de Métodos numéricos II.

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• Numerical methods II (MCMC)

• Bugs homepage. Software for Gibbs sampling.
  
• Tutorial lectures on MCMC.  Some slides from a course at the University of Southampton. (.pdf format)
• Tutorial on MCMC and Bugs.  From the 17th Workshop in Statistical Modelling, Crete.
  
• Notes on MCMC.  An introduction (.pdf format)

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• Dynamic linear models

• A course in Dynamic Linear Models by Jonathon Rougier of Durham University. (.pdf format)
• Bayesian Time Series.  A talk by Mike West from the Valencia 7 conference. (.pdf format)
• An article on Dynamic Linear Models. (.pdf format)

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• Other problems

• An introduction to graphical models and Bayesian networks by Kevin Murphy.
• An introduction to graphical models. Michael Jordan's course slides. (.pdf format)
  
• Bayes linear methods homepage.  From Durham University.
• Sets of prior probabilities and Bayesian robustness by Luis Raul Perrichi.
  

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