Here we provide a limited selection of exercises, with and without solutions, for most chapters in the book.

Many of the exercises are based on adapting examples in the book. The data and existing model code for these examples can be downloaded from the examples page.

Chapter 1 – Introduction: probability and parameters

(no exercises yet)

Chapter 2 – Monte Carlo simulations using BUGS

• Coin tossing: odc (solutions) | html (solutions)
• “How many” trick: odc (solutions) | html (solutions)

Chapter 3 – Introduction to Bayesian inference

• HIV test: odc (solutions) | html (solutions)
• Heart transplant cost-effectiveness: odc (solutions) | html (solutions)

Chapter 4 – Introduction to Markov chain Monte Carlo methods

• Student t: odc (solutions) | html (solutions)

Chapter 5 – Prior distributions

• Trams: PDF (solutions)

Chapter 6 – Regression models

• Beetles: odc (solutions)

Chapter 7 – Categorical data

• Tea tasting: odc (solutions)
• Asthma: odc (solutions)
• Asthma with treatment effect: odc (solutions)
• Kidney transplants: odc (solutions)

Chapter 8 – Model checking and comparison

• Dugongs: odc (solutions)
• Variable selection using MCMC: cystic fibrosis genetics: odc (solutions)

Chapter 9 – Issues in Modelling

(no exercises yet)

Chapter 10 – Hierarchical models

• Students’ goals: odc (solutions)

Chapter 11 – Specialised models

• Mixture models for eye tracking: odc (solutions)
• Dirichlet process mixture for eye tracking data: odc (solutions)
• Leukaemia: semiparametric survival models: odc (solutions)
• Stagnant water: splines: odc (solutions)

Chapter 12 – Different implementations of BUGS

(no exercises yet)