Bayesian Analysis

Apply Bayesian statistical methods for inference, prediction, and decision making. Learn to specify priors, compute posteriors, and interpret results in the Bayesian framework.

Usage

Ask about Bayesian methods for your analysis problem, prior selection, or interpreting posterior distributions.

Examples

• "How do I choose a prior for my Bayesian analysis?"
• "Explain the difference between Bayesian and frequentist inference"
• "Apply Bayes' theorem to this medical testing scenario"

Guidelines

• Choose priors that reflect genuine prior knowledge or are weakly informative
• Perform sensitivity analysis to check how prior choice affects conclusions
• Use conjugate priors when possible for analytical tractability
• Report the full posterior distribution, not just point estimates
• Bayesian methods naturally handle uncertainty quantification