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Buchcover - Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science - ISBN 978-1-118-91475-5
„The clear and accessible style of this second editionmakes this book ideal for all forensic scientists, appliedstatisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decisionanalysis. It will also appeal to lawyers and other scientists andprofessionals interested in the evaluation and interpretation offorensic findings, including decision making based on scientificinformation.“ (Zentralblatt MATH, 1 October2014)
Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science
von Franco Taroni, Alex Biedermann, Silvia Bozza, Paolo Garbolino und C. G. G. Aitken„This book should have a place on the bookshelf of everyforensic scientist who cares about the science of evidenceinterpretation“
Dr. Ian Evett, Principal Forensic Services Ltd, London, UK
Continuing developments in science and technology mean that theamounts of information forensic scientists are able to provide forcriminal investigations is ever increasing.
The commensurate increase in complexity creates difficulties forscientists and lawyers with regard to evaluation andinterpretation, notably with respect to issues of inference anddecision.
Probability theory, implemented through graphical methods, andspecifically Bayesian networks, provides powerful methods to dealwith this complexity. Extensions of these methods to elements
of decision theory provide further support and assistance to thejudicial system.
Bayesian Networks for Probabilistic Inference and DecisionAnalysis in Forensic Science provides a unique and comprehensiveintroduction to the use of Bayesian decision networks for theevaluation and interpretation of scientific findings in forensicscience, and for the support of decision-makers in their scientificand legal tasks.
* Includes self-contained introductions to probabilityand decision theory.
* Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decisionmodels.
* Features implementation of the methodology withreference to commercial and academically available software.
* Presents standard networks and their extensions thatcan be easily implemented and that can assist in the reader'sown analysis of real cases.
* Provides a technique for structuring problems andorganizing data based on methods and principles of scientificreasoning.
* Contains a method for the construction of coherent anddefensible arguments for the analysis and evaluation of scientificfindings and for decisions based on them.
* Is written in a lucid style, suitable for forensicscientists and lawyers with minimal mathematical background.
* Includes a foreword by Ian Evett.
The clear and accessible style of this second edition makes thisbook ideal for all forensic scientists, applied statisticians andgraduate students wishing to evaluate forensic findings from theperspective of probability and decision analysis. It will alsoappeal to lawyers and other scientists and professionals interestedin the evaluation and interpretation of forensic findings, including decision making based on scientific information.
Dr. Ian Evett, Principal Forensic Services Ltd, London, UK
Continuing developments in science and technology mean that theamounts of information forensic scientists are able to provide forcriminal investigations is ever increasing.
The commensurate increase in complexity creates difficulties forscientists and lawyers with regard to evaluation andinterpretation, notably with respect to issues of inference anddecision.
Probability theory, implemented through graphical methods, andspecifically Bayesian networks, provides powerful methods to dealwith this complexity. Extensions of these methods to elements
of decision theory provide further support and assistance to thejudicial system.
Bayesian Networks for Probabilistic Inference and DecisionAnalysis in Forensic Science provides a unique and comprehensiveintroduction to the use of Bayesian decision networks for theevaluation and interpretation of scientific findings in forensicscience, and for the support of decision-makers in their scientificand legal tasks.
* Includes self-contained introductions to probabilityand decision theory.
* Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decisionmodels.
* Features implementation of the methodology withreference to commercial and academically available software.
* Presents standard networks and their extensions thatcan be easily implemented and that can assist in the reader'sown analysis of real cases.
* Provides a technique for structuring problems andorganizing data based on methods and principles of scientificreasoning.
* Contains a method for the construction of coherent anddefensible arguments for the analysis and evaluation of scientificfindings and for decisions based on them.
* Is written in a lucid style, suitable for forensicscientists and lawyers with minimal mathematical background.
* Includes a foreword by Ian Evett.
The clear and accessible style of this second edition makes thisbook ideal for all forensic scientists, applied statisticians andgraduate students wishing to evaluate forensic findings from theperspective of probability and decision analysis. It will alsoappeal to lawyers and other scientists and professionals interestedin the evaluation and interpretation of forensic findings, including decision making based on scientific information.
