Why the scale is the reader's problem | The check | The anchored curve | Run-to-run noise | The chosen scale versus the data | Cost and samplers

Introduction | What the evidence settles | Are the conditional predictions calibrated? | Checking the joint distribution with simulate() | What the three checks answer | Next steps

Introduction | Example fit | Convergence diagnostics | Diagnostics for edge-selected parameters | Traceplots | Spike-and-slab summaries | Bayes factors | NUTS diagnostics | E-BFMI | Divergent transitions | Tree depth | Non-reversible steps | Warmup and equilibration | Hierarchical prior trust gauge | The two alarms | Fits that skip the approximation instead | What to do when a chain is flagged | Next steps

The models | A worked example | What the fit contains | Which edges the evidence settles | The edge evidence plot | Priors | The Gaussian and mixed members | Comparing groups | Where to go next | References

Introduction | ADHD dataset | Fitting a model | Posterior summaries | Visualizing the groups | Next steps | References