Risk Assessment and Decision Analysis with Bayesian Networks

by Norman Fenton, Martin Neil

Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features A dedicated contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.

Genres: Mathematics, Reference

660 pages, Hardcover

First published August 3, 2012

Reviews

[Luis Detlefsen · Rating 5 out of 5]

I started reading it because it explains very well the Monty Hall problem.

It explains very well the Bayesian networks, all the theory and a bunch of detailed examples. This book actually made me like Bayesian networks and really understand the applications of it.

[Joe Hightower · Rating 4 out of 5]

Very informative, but too much like a manual for the author's software. Aside from that it is a very useful description of how to construct complex Bayesian Networks