Standard syllabus
Bayesian statistics · Undergraduate · Statistics
Topics
Bayesian foundations
- Subjective probability and Bayes' theorem
- Prior, likelihood, and posterior
- Conjugate priors: beta-binomial, normal-normal
- Credible intervals vs confidence intervals
- Bayesian hypothesis testing (introduction)
Computation and models
- Posterior simulation: Monte Carlo methods
- Introduction to MCMC: Metropolis–Hastings and Gibbs
- Bayesian linear and logistic regression
- Model comparison: Bayes factors (intro)
- Sensitivity to prior choice
Applications
- Hierarchical models (introduction)
- Empirical Bayes methods
- Bayesian model averaging (overview)
- Communicating posterior uncertainty
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$60.00 · 60 min · Undergraduate · Online ($60/hr)
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