Applications of Bayesian Networks

18 Pages Posted: 9 Nov 2012 Last revised: 29 May 2020

See all articles by Ron S. Kenett

Ron S. Kenett

KPA Ltd.; The Samuel Neaman Institute, Technion; University of Turin and College Carlo Alberto

Date Written: November 8, 2012

Abstract

Modelling cause and effect relationships has been a major challenge for statisticians in a wide range of application areas. Bayesian Networks (BN) combine graphical analysis with Bayesian analysis to represent causality maps linking measured and target variables. Such maps can be used for diagnostics and predictive analytics. The paper presents an introduction to Bayesian Networks and various applications such as the impact of management style on statistical efficiency (Kenett1), studies of web site usability (Kenett2), operational risks (Kenett3), biotechnology (Peterson4), customer satisfaction surveys (Kenett5), healthcare systems (Kenett6) and the testing of web services (Bai7). Following the presentation of these case studies, a general section discusses various properties of Bayesian Networks. Some references to software programs used to construct BNs are also provided. A concluding section lists some possible directions for future research.

Keywords: applied statistics, Bayesian network, descriptive causality, diagnostics, predictive analysis, decision support systems

JEL Classification: A10, C11, C13, C30, C61, C67, D80

Suggested Citation

Kenett, Ron S., Applications of Bayesian Networks (November 8, 2012). Available at SSRN: https://ssrn.com/abstract=2172713 or http://dx.doi.org/10.2139/ssrn.2172713

Ron S. Kenett (Contact Author)

KPA Ltd. ( email )

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The Samuel Neaman Institute, Technion ( email )

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