Combining uncertainties in a court of law using Bayesian networks

dc.contributor.authorMuller, M. A.en_ZA
dc.date.accessioned2018-03-16T09:14:33Z
dc.date.available2018-03-16T09:14:33Z
dc.date.issued2017
dc.descriptionCITATION: Muller, M. A. 2017. Combining uncertainties in a court of law using Bayesian networks. Obiter, 38(3): 505-516.
dc.descriptionThe original publication is available at http://journals.co.za/content/journal/10520/EJC-d1fd72038
dc.description.abstractPeople generally have difficulty dealing with the counter-intuitive notion of probability, and therefore they often misunderstand aspects of uncertainty. This is particularly significant in a court of law when for example an estimate of the probability of the evidence gets confused with an estimate of the probability of guilt. The circumstantial evidence is especially prone to being handled incorrectly. Professor Fenton at the Queen Mary University of London said, “You could argue that virtually every case with circumstantial evidence is ripe for being improved by Bayesian arguments”.1 In this paper, the evidence in a famous court case is revisited in the context of Bayesian networks.en_ZA
dc.description.urihttp://journals.co.za/content/journal/10520/EJC-d1fd72038
dc.description.versionPost print
dc.format.extent10 pages
dc.identifier.citationMuller, M. A. 2017. Combining uncertainties in a court of law using Bayesian networks. Obiter, 38(3): 505-516
dc.identifier.issn1682-5853 (print)
dc.identifier.urihttp://hdl.handle.net/10019.1/103226
dc.language.isoen_ZAen_ZA
dc.publisherObiter Law Journal: Nelson Mandela Metropolitan University (NMMU), Faculty of Law
dc.rights.holderAuthor retains copyright
dc.subjectBayesian networksen_ZA
dc.titleCombining uncertainties in a court of law using Bayesian networksen_ZA
dc.typeArticleen_ZA
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
muller_combining_2017.pdf
Size:
470.27 KB
Format:
Adobe Portable Document Format
Description:
Download article
License bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.95 KB
Format:
Item-specific license agreed upon to submission
Description: