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Bayesian Regression Modeling via MCMC Techniques – Statistics.Com

0-6 MonthOnline
OnlineBusiness Analytics
Online Self Paced1100
4.5 (90%) 2 votes
DescriptionProgram StructureEligibilityToolsFacultyContact

In this online course, students will learn how to apply Markov Chain Monte Carlo techniques (MCMC) to Bayesian statistical modeling using WinBUGS and R software.

Topics covered include Gibbs sampling and the Metropolis-Hastings method. Participants will also learn how to implement linear regression (normal and t errors), poisson and loglinear regression, and binary/binomial regression using WinBUGS.

Course Program:

  • Week 1: Using Markov Chain Monte Carlo
  • Week 2: Sampling From Priors
  • Week 3: Linear Regression Modeling in WinBUGS
  • Week 4: General Linear Modeling in WinBUGS

Important Date:

April 24, 2015 to May 22, 2015


4 Weeks

Time Requirement:

About 15 hours per week, at times of  your choosing.


INR 37,740 (assuming $ = INR 60)

Part Time/Full Time:

Part Time

Statisticians and analysts who need to build statistical models of data.

  • R
  • WinBUGS
  • Dr. Peter Congdon
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