Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: * An introduction to Dirichlet Distribution, Exponential Families and their applications. * A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. * A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. * All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer