- Motivations, frameworks for inference, probability
- Introduction
- Inference frameworks
- Likelihood
- Priors and posteriors
- Starting linear models, priors, sampling
- Bayesian workflow
- Prior predictive simulation
- Sampling
- Diagnostics and posteriors
- Modular linear models
- Modular models
- Bivariate models
- Multiple regression
- Drawing conclusions
- Model evaluation, diagnosing sampling problems
- Sampling challenges
- Model improvements
- Summarizing models
- Convenience packages
- Model comparison
- Hypothesis testing
- WAIC
- PSIS-LOOCV
- Model averaging
-
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