Bayesian decision analysis supports principled decision making in complex domains. This textbook takes the reader from a formal analysis of simple decision problems to a careful analysis of the sometimes very complex and data rich structures confronted by practitioners. The book contains basic material on subjective probability theory and multi-attribute utility theory event and decision trees Bayesian networks influence diagrams and causal Bayesian networks. The author demonstrates when and how the theory can be successfully applied to a given decision problem how data can be sampled and expert judgements elicited to support this analysis and when and how an effective Bayesian decision analysis can be implemented. Evolving from a third-year undergraduate course taught by the author over many years all of the material in this book will be accessible to a student who has completed introductory courses in probability and mathematical statistics. Language: English