Wednesday, 5 September 2012

Introduction to Bayesian Computing and Techniques

Bayesian methods, recently unleashed by computing power, have become very popular.  They answer questions like "given the state of the world, what is the probability that...?"  These are often more useful questions than those starting with "given the null hypothesis, ..."

Get your hands on Bayesian computing with Peter Congdon's online course "An Introduction to Bayesian Computing and Techniques" at For more details please visit at

Participants in "An Introduction to Bayesian Computing and Techniques" will learn why Bayesian computing has gained wide popularity, and how to apply Markov Chain Monte Carlo techniques (MCMC) to Bayesian statistical modeling using WinBUGS software. Participants will learn how to use WinBUGS software, use it to estimate parameters of standard distributions, and implement simple regression models.  This course is recommended as a lead-in to "Bayesian Regression Modeling via MCMC," also with Dr. Congdon.

Who Should Take This Course:
Statistical analysts and consultants who need to make decisions (or advise decision-makers) via a process that incorporates domain-specific information -- not simply abstract and arbitrary statistical rules.

Course Program:

Course outline: The course is structured as follows

  • Basic ideas of MCMC
  • Benefits of Bayes methods
  • Priors and Prior Informativeness
  • Important distributions in Bayesian analysis
  • Introduction to three standard schemes: (normal data, normal prior; binomial data, beta prior; poisson data, gamma prior)

  • Winbugs syntax and programs, data inputs, convergence checks, obtaining summaries

  • Main elements of posterior summarization
  • Tests on parameters or parameter collections (posterior probability tests)
  • Model predictions

  • Simple regression models (normal, binary & binomial, poisson)

Dr. Peter Congdon is a Research Professor in Quantitative Geography and Health Statistics at Queen Mary University of London. He is the author of "Bayesian Statistical Modeling, Applied Bayesian Modeling," and "Bayesian Models for Categorical Data," all published by Wiley, as well as numerous articles in peer-reviewed journals. His research interests include spatial data analysis, Bayesian statistics, latent variable models and epidemiology. Participants can ask questions and exchange comments with Dr. Congdon via a private discussion board throughout the period.

You will be able to ask questions and exchange comments with Dr. Michael Chernick and Dr. Robert LaBudde via a private discussion board throughout the course.   The courses take place online at in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at

Call: 020 66009116


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