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Expert Evidence and Criminal Justice$
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Mike Redmayne

Print publication date: 2001

Print ISBN-13: 9780198267805

Published to Oxford Scholarship Online: January 2010

DOI: 10.1093/acprof:oso/9780198267805.001.0001

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Probability Models in Forensic Science

Probability Models in Forensic Science

Chapter:
(p.36) 3 Probability Models in Forensic Science
Source:
Expert Evidence and Criminal Justice
Author(s):

MIKE REDMAYNE

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198267805.003.0003

This chapter begins by examining in detail the important role that interpretation plays in forensic science. It suggests two reasons for stressing interpretation: the significance of trace evidence often depends on the information available to the forensic scientist and on the assumptions he brings to his work, and the way the evidence is used in court. It discusses the importance of Bayesianism in forensic science and how it offers insights that classical statistics do not, which make it appear to offer decision-makers more accurate information about the value of scientific evidence. It explains that the use of fingerprint evidence may give absolute identifications. It also explores several probability models in forensic science.

Keywords:   probability models, forensic science, trace evidence, Bayesianism, classical statistics, interpretation

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