Bayesian Statistics: Course Outline

• Prior information.
• Prior distribution. 
• Posterior distributions. 
• The posterior means.
• Medians (Bayes estimators under loss functions).
• Variances of univariate and bivariate posterior distributions. 
• Non-informative priors.
• Methods of elicitation of hyper parameters of informative priors. 
• Bayesian Hypotheses Testing: Bayes factor.
• The highest density region.
• Posterior probability of the hypothesis.

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