Bayesian Statistics
Bayesian inference from priors to posteriors, with conjugate models, hierarchical models and Markov chain Monte Carlo.
STAT-361 Year 3 3 credits 12 lessons planned ▶ Video lessons coming soon
Offered by HSM University · Statistics
Course content
- 1The Bayesian approachComing
- 2Bayes' theorem for parametersComing
- 3Conjugate priorsComing
- 4Choosing priorsComing
- 5Posterior summaries and credible intervalsComing
- 6Predictive distributionsComing
- 7Hierarchical modelsComing
- 8Markov chain Monte Carlo: Metropolis–HastingsComing
- 9Gibbs sampling and convergenceComing
- 10Bayesian regressionComing
- 11Model checking and comparisonComing
- 12Capstone: a Bayesian analysis with modern softwareComing
Requirements
Recommended background. You can start any course at any time.
Description
Bayesian inference from priors to posteriors, with conjugate models, hierarchical models and Markov chain Monte Carlo.
Part of the Science stream, typically taken in year 3.