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Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Author: Franco Taroni

Publisher: John Wiley & Sons

Published: 2014-09-22

Total Pages: 472

ISBN-13: 0470979739

Bayesian Networks “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 Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science Second Edition 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 diffculties 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 and Probabilistic Inference in Forensic Science

Author:

Publisher:

Published: 2006

Total Pages: 354

ISBN-13: 9780470091746

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Data Analysis in Forensic Science

Author: Franco Taroni

Publisher: John Wiley & Sons

Published: 2010-03-19

Total Pages: 388

ISBN-13: 9780470665077

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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.

Bayes Factors for Forensic Decision Analyses with R

Author: Silvia Bozza

Publisher: Springer Nature

Published: 2022-10-31

Total Pages: 196

ISBN-13: 3031098390

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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 perspective, practical relevance, and applicability—keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics: Probabilistic Inference - Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence. Decision Making - Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law. Operational Relevance - Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context. Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes' theorem providing the fundamental logical tenet for assessing how new information—scientific evidence—ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist's thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty. This book would be relevant to students, practitioners, and applied statisticians interested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes. This book is Open Access.

Encyclopedia of Forensic Sciences

Author:

Publisher: Academic Press

Published: 2012-12-28

Total Pages: 2253

ISBN-13: 0123821665

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Forensic science includes all aspects of investigating a crime, including: chemistry, biology and physics, and also incorporates countless other specialties. Today, the service offered under the guise of "forensic science’ includes specialties from virtually all aspects of modern science, medicine, engineering, mathematics and technology. The Encyclopedia of Forensic Sciences, Second Edition, Four Volume Set is a reference source that will inform both the crime scene worker and the laboratory worker of each other’s protocols, procedures and limitations. Written by leading scientists in each area, every article is peer reviewed to establish clarity, accuracy, and comprehensiveness. As reflected in the specialties of its Editorial Board, the contents covers the core theories, methods and techniques employed by forensic scientists – and applications of these that are used in forensic analysis. This 4-volume set represents a 30% growth in articles from the first edition, with a particular increase in coverage of DNA and digital forensics Includes an international collection of contributors The second edition features a new 21-member editorial board, half of which are internationally based Includes over 300 articles, approximately 10pp on average Each article features a) suggested readings which point readers to additional sources for more information, b) a list of related Web sites, c) a 5-10 word glossary and definition paragraph, and d) cross-references to related articles in the encyclopedia Available online via SciVerse ScienceDirect. Please visit www.info.sciencedirect.com for more information This new edition continues the reputation of the first edition, which was awarded an Honorable Mention in the prestigious Dartmouth Medal competition for 2001. This award honors the creation of reference works of outstanding quality and significance, and is sponsored by the RUSA Committee of the American Library Association

Forensic DNA Trace Evidence Interpretation

Author: Duncan Taylor

Publisher: CRC Press

Published: 2023-05-30

Total Pages: 565

ISBN-13: 1000801411

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Forensic DNA Trace Evidence Interpretation: Activity Level Propositions and Likelihood Ratios provides all foundational information required for a reader to understand the practice of evaluating forensic biology evidence given activity level propositions and to implement the practice into active casework within a forensic institution. The book begins by explaining basic concepts and foundational theory, pulling together research and studies that have accumulated in forensic journal literature over the last 20 years. The book explains the laws of probability - showing how they can be used to derive, from first principles, the likelihood ratio - used throughout the book to express the strength of evidence for any evaluation. Concepts such as the hierarchy of propositions, the difference between experts working in an investigative or evaluative mode and the practice of case assessment and interpretation are explained to provide the reader with a broad grounding in the topics that are important to understanding evaluation of evidence. Activity level evaluations are discussed in relation to biological material transferred from one object to another, the ability for biological material to persist on an item for a period of time or through an event, the ability to recover the biological material from the object when sampled for forensic testing and the expectations of the prevalence of biological material on objects in our environment. These concepts of transfer, persistence, prevalence and recovery are discussed in detail in addition to the factors that affect each of them. The authors go on to explain the evaluation process: how to structure case information and formulate propositions. This includes how a likelihood ratio formula can be derived to evaluate the forensic findings, introducing Bayesian networks and explaining what they represent and how they can be used in evaluations and showing how evaluation can be tested for robustness. Using these tools, the authors also demonstrate the ways that the methods used in activity level evaluations are applied to questions about body fluids. There are also chapters dedicated to reporting of results and implementation of activity level evaluation in a working forensic laboratory. Throughout the book, four cases are used as examples to demonstrate how to relate the theory to practice and detail how laboratories can integrate and implement activity level evaluation into their active casework.

Statistics and Probability in Forensic Anthropology

Author: Zuzana Obertová

Publisher: Academic Press

Published: 2020-07-28

Total Pages: 434

ISBN-13: 0128157658

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Statistics and Probability in Forensic Anthropology provides a practical guide for forensic scientists, primarily anthropologists and pathologists, on how to design studies, how to choose and apply statistical approaches, and how to interpret statistical outcomes in the forensic practice. As with other forensic, medical and biological disciplines, statistics have become increasingly important in forensic anthropology and legal medicine, but there is not a single book, which specifically addresses the needs of forensic anthropologists in relation to the research undertaken in the field and the interpretation of research outcomes and case findings within the setting of legal proceedings. 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 statistical approaches addressing measurement errors and reliability. Scientific terminology understandable to students and advanced practitioners of forensic anthropology, pathology and related disciplines is used throughout. Additionally, Statistics and Probability in Forensic Anthropology facilitates sufficient understanding of the statistical procedures and data interpretation based on statistical outcomes and models, which helps the reader confidently present their work within the forensic context, either in the form of case reports for legal purposes or as research publications for the scientific community. Contains the application of both frequentist and Bayesian statistics in relation to topics relevant for forensic anthropology research and the interpretation of findings Provides examples of study designs and their statistical solutions, partly following the layout of scientific manuscripts on common topics in the field Includes scientific terminology understandable to students and advanced practitioners of forensic anthropology, legal medicine and related disciplines

Bayesian Networks

Author: Olivier Pourret

Publisher: John Wiley & Sons

Published: 2008-04-30

Total Pages: 446

ISBN-13: 9780470994542

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Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. 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 sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.

Bayesian Networks

Author: Olivier Pourret

Publisher: John Wiley & Sons

Published: 2008-05-05

Total Pages: 446

ISBN-13: 0470060301

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Interactive Collaborative Information Systems

Author: Robert Babuška

Publisher: Springer

Published: 2010-03-22

Total Pages: 598

ISBN-13: 3642116884

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The increasing complexity of our world demands new perspectives on the role of technology in decision making. Human decision making has its li- tations in terms of information-processing capacity. We need new technology to cope with the increasingly complex and information-rich nature of our modern society. This is particularly true for critical environments such as crisis management and tra?c management, where humans need to engage in close collaborations with arti?cial systems to observe and understand the situation and respond in a sensible way. We believe that close collaborations between humans and arti?cial systems will become essential and that the importance of research into Interactive Collaborative Information Systems (ICIS) is self-evident. Developments in information and communication technology have ra- cally changed our working environments. The vast amount of information available nowadays and the wirelessly networked nature of our modern so- ety open up new opportunities to handle di?cult decision-making situations such as computer-supported situation assessment and distributed decision making. To make good use of these new possibilities, we need to update our traditional views on the role and capabilities of information systems. The aim of the Interactive Collaborative Information Systems project is to develop techniques that support humans in complex information en- ronments and that facilitate distributed decision-making capabilities. ICIS emphasizes the importance of building actor-agent communities: close c- laborations between human and arti?cial actors that highlight their comp- mentary capabilities, and in which task distribution is ?exible and adaptive.