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 to cope adequately with the problems it causes, or to make the required inferences. Probability theory, implemented through graphical methods, specifically Bayesian networks, offers a powerful tool to deal with this complexity, and discover valid patterns in data. Bayesian Networks and Probabilistic Inference in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian networks for the evaluation of scientific evidence in forensic science. 
<ul>
<li>Includes self-contained introductions to both Bayesian networks and probability.</li> <li>Features implementation of the methodology using HUGIN, the leading Bayesian networks software.</li> <li>Presents basic standard networks that can be implemented in commercially and academically available software packages, and that form the core models necessary for the reader’s own analysis of real cases.</li> <li>Provides a technique for structuring problems and organizing uncertain data based on methods and principles of scientific reasoning.</li> <li>Contains a method for constructing coherent and defensible arguments for the analysis and evaluation of forensic evidence.</li> <li>Written in a lucid style, suitable for forensic scientists with minimal mathematical background.</li> <li>Includes a foreword by David Schum.</li> </ul>
The clear and accessible style makes this book ideal for all forensic scientists and applied statisticians working in evidence evaluation, as well as graduate students in these areas. It will also appeal to scientists, lawyers and other professionals interested in the evaluation of forensic evidence and/or Bayesian networks.

Bayesian Networks and Probabilistic Inference in Forensic Science

Science & Math

Taroni, Franco

Biedermann, Alex

Garbolino, Paolo

Aitken, Colin

Mathematics

wiley

The first edition of Statistics and the Evaluation of Evidence for Forensic Scientists established itself as a highly regarded authority on this area. Fully revised and updated, the second edition provides significant new material on areas of current interest including: 
<ul>
<li>Glass Interpretation</li> <li>Fibres Interpretation</li> <li> Bayes’ Nets </li> </ul>
The title presents comprehensive coverage of the statistical evaluation of forensic evidence. It is written with the assumption of a modest mathematical background and is illustrated throughout with up-to-date examples from a forensic science background. The clarity of exposition makes this book ideal for all forensic scientists, lawyers and other professionals in related fields interested in the quantitative assessment and evaluation of evidence. 'There can be no doubt that the appreciation of some evidence in a court of law has been greatly enhanced by the sound use of statistical ideas and one can be confident that the next decade will see further developments, during which time this book will admirably serve those who have cause to use statistics in forensic science.' D.V. Lindley

Statistics and the Evaluation of Evidence for Forensic Scientists

A practical guide for determining the evidential value of physicochemical data Microtraces of various materials (e.g. glass, paint, fibres, and petroleum products) are routinely subjected to physicochemical examination by forensic experts, whose role is to evaluate such physicochemical data in the context of the prosecution and defence propositions. Such examinations return various kinds of information, including quantitative data. From the forensic point of view, the most suitable way to evaluate evidence is the likelihood ratio. This book provides a collection of recent approaches to the determination of likelihood ratios and describes suitable software, with documentation and examples of their use in practice. The statistical computing and graphics software environment R, pre-computed Bayesian networks using Hugin Researcher and a new package, calcuLatoR, for the computation of likelihood ratios are all explored. Statistical Analysis in Forensic Science will provide an invaluable practical guide for forensic experts and practitioners, forensic statisticians, analytical chemists, and chemometricians. Key features include: <ul>
<li>Description of the physicochemical analysis of forensic trace evidence.</li> <li>Detailed description of likelihood ratio models for determining the evidential value of multivariate physicochemical data.</li> <li>Detailed description of methods, such as empirical cross-entropy plots, for assessing the performance of likelihood ratio-based methods for evidence evaluation.</li> <li>Routines written using the open-source R software, as well as Hugin Researcher and calcuLatoR.</li> <li>Practical examples and recommendations for the use of all these methods in practice. </li> </ul>

Statistical Analysis in Forensic Science: Evidential Value of Multivariate Physicochemical Data

Ramos, Daniel

Martyna, Agnieszka

Zadora, Grzegorz

"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.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science (Statistics in Practice)

Bozza, Silvia

This is the first text to examine the use of statistical methods in forensic science and bayesian statistics in combination. 
The book is split into two parts: Part One concentrates on the philosophies of statistical inference. Chapter One examines the differences between the frequentist, the likelihood and the Bayesian perspectives, before Chapter Two explores the Bayesian decision-theoretic perspective further, and looks at the benefits it carries. Part Two then introduces the reader to the practical aspects involved: the application, interpretation, summary and presentation of data analyses are all examined from a Bayesian decision-theoretic perspective. A wide range of statistical methods, essential in the analysis of forensic scientific data is explored. These include the comparison of allele proportions in populations, the comparison of means, the choice of sampling size, and the discrimination of items of evidence of unknown origin into predefined populations. Throughout this practical appraisal there are a wide variety of examples taken from the routine work of forensic scientists. These applications are demonstrated in the ever-more popular R language. The reader is taken through these applied examples in a step-by-step approach, discussing the methods at each stage.

Data Analysis in Forensic Science: A Bayesian Decision Perspective

Statistics in Practice A new series of practical books outlining the use of statistical techniques in a wide range of application areas: 
<ul>
<li>Human and Biological Sciences</li> <li>Earth and Environmental Sciences</li> <li>Industry, Commerce and Finance</li> </ul> The use of statistical and probabilistic methods and models in forensic science is of increasing importance, as demonstrated by the widespread public interest in DNA profiling evidence. However, such methods and models are appropriate to a range of other situations also of relevance to forensic scientists. Assuming only a modest mathematical background, the book uses data-based examples from a forensic science background to illustrate, with careful presentation and explanation, the relevant statistical concepts and methods. Topics covered include: <ul>
<li>Transfer evidence.</li> <li>The likelihood ratio approach for evaluating evidence under conflicting hypotheses produced by the prosecution and the defence.</li> <li>The interpretation of quantitative results—the prosecutor’s and the defender’s fallacies.</li> <li>The examination of DNA profiling, blood groups, glass fragments, etc.</li> </ul> The clarity of exposition makes this book ideal for all forensic scientists, lawyers and other professionals in related fields interested in the quantitative assessment and evaluation of evidence.

Statistics and the Evaluation of Evidence for Forensic Scientists (Statistics in Practice)

Statistics and the Evaluation of Evidence for Forensic Scientists The leading resource in the statistical evaluation and interpretation of forensic evidence The third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That's why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It's written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence. <ul> <li>Discusses the entire chain of reasoning-from evidence pre-assessment to court presentation;</li> <li>Includes material for the understanding of evidence interpretation for single and multiple trace evidence;</li> <li>Provides real examples and data for improved understanding.</li> </ul> Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. 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.

See the best price to sell, buy, or rent books by Aitken, Colin. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Aitken, Colin

See the best price to sell, buy, or rent books by Aitken, Colin. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Bayesian Networks and Probabilistic Inference in Forensic Science

Statistics and the Evaluation of Evidence for Forensic Scientists

Statistical Analysis in Forensic Science: Evidential Value of Multivariate Physicochemical Data

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science (Statistics in Practice)

Data Analysis in Forensic Science: A Bayesian Decision Perspective

Statistics and the Evaluation of Evidence for Forensic Scientists (Statistics in Practice)

Statistics and the Evaluation of Evidence for Forensic Scientists (Statistics in Practice)