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Probability and Forensic Evidence: Theory, Philosophy, and Applications

ISBN13: 9781108449144
Published: April 2021
Publisher: Cambridge University Press
Country of Publication: UK
Format: Paperback
Price: £31.99
Hardback edition , ISBN13 9781108428279

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This book addresses the role of statistics and probability in the evaluation of forensic evidence, including both theoretical issues and applications in legal contexts. It discusses what evidence is and how it can be quantified, how it should be understood, and how it is applied (and, sometimes, misapplied). After laying out their philosophical position, the authors begin with a detailed study of the likelihood ratio. Following this grounding, they discuss applications of the likelihood ratio to forensic questions, in the abstract and in concrete cases. The analysis of DNA evidence in particular is treated in great detail. Later chapters concern Bayesian networks, frequentist approaches to evidence, the use of belief functions, and the thorny subject of database and familial search. Finally, the authors provide commentary on various recommendation reports for forensic science. Written to be accessible to a wide audience of applied mathematicians, forensic scientists, and scientifically-oriented legal scholars, this book is a must-read for all those interested in the mathematical and philosophical foundations of evidence and belief.

Key Features:

  • Gathers all the important aspects of statistical evidence evaluation in one volume, including the first in-depth treatment of the likelihood ratio
  • Written with minimal mathematical prerequisites and more concerned with concepts than technical calculations
  • Of interest to a wide audience including applied mathematicians and statisticians, forensic scientists, and scientifically-oriented legal scholars

1. Some Philosophy of Probability, Statistics, and Forensic Science
2. Evidence and the Likelihood Ratio
3. The Uncertainty of the Likelihood Ratio
4. Forensic Identification
5. The Bayesian Framework in Legal Cases
6. Bayesian Networks
7. DNA
8. Statistical Modeling and DNA Mixture Evaluation
9. p-Values of Likelihood Ratios
10. From Evidence to Decision
11. The Interpretation of DNA Database Matches
12. Familial Searching
13. Belief Functions and their Applications
14. Recommendation Reports