"This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation" Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. • Includes self-contained introductions to probability and decision theory. • Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. • Features implementation of the methodology with reference to commercial and academically available software. • Presents standard networks and their extensions that can be easily implemented and that can assist in the reader’s own analysis of real cases. • Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. • Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. • Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. • Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.
The amount of information forensic scientists are able to offer is ever increasing, owing to vast developments in science and technology. Consequently, the complexity of evidence does not allow scientists...
It was initially developed by two statisticians, J. Neyman (1894–1981) and E.S. Pearson (1895–1980). A null hypothesis or working hypothesis is established and data are collected to test this hypothesis with the use of a statistic, ...
Bayesian Networks and Probabilistic Inference in Forensic Science
Bayes Factors for Forensic Decision Analyses with R provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational ...
In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.
The book includes the application of both frequentist and Bayesian statistics in relation to topics relevant for the research and the interpretation of findings in forensic anthropology, as well as general chapters on study design and ...
... Bayesian Networks and Probabilistic Inference in Forensic Science, 2nd ed. John Wiley & Sons, Chichester, UK. Tribe, L.H. (1971). Trial by Mathematics. Harvard Law Review, 84, 1329. Detailed coverage of the probabilistic and ...
This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural ...
In The Use of Statistics in Forensic Science, C.G.G. Aitken, and D.A. Stoney, editors, pages 55–106. Ellis Horwood, Chichester, U.K., 1991. Hubert, L., and Wainer, H. A Statistical Guide of the Ethically Perplexed.
Philip Maynard is a senior lecturer with the Centre for Forensic Science at the University of Technology Sydney. He teaches the Crime Scene ... After teaching in the field of textile technology she moved to forensic science.