Probability and Forensic Evidence
Theory, Philosophy, and Applications

A self-contained examination of all aspects of statistical evidence evaluation in forensic science, from theory to concrete applications.

Ronald Meester (Author), Klaas Slooten (Author)

9781108428279, Cambridge University Press

Hardback, published 8 April 2021

424 pages
24 x 16 x 3 cm, 0.96 kg

'This book is accessible to anyone … It provides an example of applied math being utilized in the real world while being mindful of the gap that can occur between practice and theory. The diligent reader will find much to learn and enjoy throughout.' Notices of the American Mathematical Society

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 searches and familial searching. 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.

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
References
Index.

Subject Areas: Probability & statistics [PBT], Legal system: general [LNA], Forensic science [JKVF1], Social research & statistics [JHBC]