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Risk assessment and decision analysis with Bayesian networks

Author: Norman E Fenton; Martin Neil
Publisher: Boca Raton, Florida : CRC Press, [2019] ©2019
Edition/Format:   eBook : Document : English : Second editionView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Fenton, Norman E., 1956-
Risk assessment and decision analysis with Bayesian networks.
Boca Raton, FL : CRC Press, Taylor & Francis Group, [2019]
(DLC) 2018009541
(OCoLC)1031043793
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Norman E Fenton; Martin Neil
ISBN: 9781315269405 1315269406 9781351978972 1351978977
OCLC Number: 1049801227
Description: 1 online resource (xxi, 637 pages)
Contents: Introduction --
Debunking bad statistics --
The need for causal, explanatory models in risk assessment --
Measuring uncertainty: the inevitability of subjectivity --
The basics of probability --
Bayes' theorem and conditional probability --
From Bayes' theorem to Bayesian networks --
Defining the structure of Bayesian networks --
Building and eliciting node probability tables --
Numeric variables and continuous distribution functions --
Decision analysis, decision trees, value of information analysis, and sensitivity --
Hypothesis testing and confidence intervals --
Modeling operational risk --
Systems reliability modeling --
The role of Bayes in forensic and legal evidence presentation --
Building and using Bayesian networks for legal reasoning --
Learning from data in Bayesian networks.
Responsibility: Norman Fenton, Martin Neil.

Abstract:

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.

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Praise for the first edition:"By offering many attractive examples of Bayesian networks and by making use of software that allows one to play with the networks, readers will definitely get a feel for Read more...

 
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