Data Analysis in Forensic Science

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: Description of the physicochemical analysis of forensic trace evidence. Detailed description of likelihood ratio models for determining the evidential value of multivariate physicochemical data. Detailed description of methods, such as empirical cross-entropy plots, for assessing the performance of likelihood ratio-based methods for evidence evaluation. Routines written using the open-source R software, as well as Hugin Researcher and calcuLatoR. Practical examples and recommendations for the use of all these methods in practice.

"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.

Concentrating on the natural science aspects of forensics, top international authors from renowned universities, institutes, and laboratories impart the latest information from the field. In doing so they provide the background needed to understand the state of the art in forensic science with a focus on biological, chemical, biochemical, and physical methods. The broad subject coverage includes spectroscopic analysis techniques in various wavelength regimes, gas chromatography, mass spectrometry, electrochemical detection approaches, and imaging techniques, as well as advanced biochemical, DNA-based identification methods. The result is a unique collection of hard-to-get data that is otherwise only found scattered throughout the literature.

Co-published with the American Academy of Forensic Sciences, Forensic Science presents comprehensive international discussion of key issues and future directions within the forensic sciences. Written by accomplished and respected specialists in approximately eleven distinct areas of the forensic sciences, the volume will examine central issues within each discipline, provide perspective on current debate and explore current and proposed research initiatives. It will also provide the forensically involved international community with current in-depth perspective on the key issues in the contemporary practice of the forensic sciences.

This practical guide covers the essential tasks in statistical data analysis encountered in high energy physics and provides comprehensive advice for typical questions and problems. The basic methods for inferring results from data are presented as well as tools for advanced tasks such as improving the signal-to-background ratio, correcting detector effects, determining systematics and many others. Concrete applications are discussed in analysis walkthroughs. Each chapter is supplemented by numerous examples and exercises and by a list of literature and relevant links. The book targets a broad readership at all career levels – from students to senior researchers. An accompanying website provides more algorithms as well as up-to-date information and links. * Free solutions manual available for lecturers at www.wiley-vch.de/supplements/

Forensic document examination is a long established specialty and its practitioners have regularly been shown to have acquired skills that enable them to assist the judicial process. This book, aimed primarily at students studying forensic science and document examination in particular, introduces all of the essential ideas that are to be found in the work of the forensic document examiner in a concise and straightforward way. Each examination type is described not only in terms of its procedural basis but also the science and reasoning that underpins it. The reader will be able to relate the different kinds of interpretation skills used by the document examiner to those used in other forensic disciplines. This book will be an invaluable text for all students taking courses in Forensic Science or related subjects. The book will also be a useful reference for researchers new to this field or practitioners looking for an accessible overview. The author will be adding new references that are relevant as they are published and some more worked examples from time to time. Please visit qdbook.blogspot.co.uk for more details.

DATA SCIENCE IN THEORY AND PRACTICE[/b] EXPLORE THE FOUNDATIONS OF DATA SCIENCE WITH THIS INSIGHTFUL NEW RESOURCE Data Science in Theory and Practice delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. The book offers readers a multitude of topics all relevant to the analysis of complex data sets. Along with a robust exploration of the theory underpinning data science, it contains numerous applications to specific and practical problems. The book also provides examples of code algorithms in R and Python and provides pseudo-algorithms to port the code to any other language. Ideal for students and practitioners without a strong background in data science, readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets Perfect for advanced undergraduate and graduate students in Data Science, Business Analytics, and Statistics programs, Data Science in Theory and Practice will also earn a place in the libraries of practicing data scientists, data and business analysts, and statisticians in the private sector, government, and academia.

Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science. Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes: An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.

Over the last half century, the science and practice of forensic science has undergone dramatic changes. Since the early 1960s the technological developments and their application to forensic science have been immense. Not only that, the application of science within a legal context and framework has developed enormously, as has the evaluation of the analytical results obtained. This unique text looks at the changes and challenges within forensic science over the last fifty years through a continuous diary of development witnessed by the editorials and relevant correspondence delivered through the UK Forensic Science Societies’ journal Science and Justice (formally the Journal of the Forensic Science Society). The editorials are divided into sections relating to the developments of forensic practice, the advancement of science, education, legal aspects, forensic science and medicine, the international dimension of forensic science and the interpretation and evaluation of evidence. The text and first two sections are set in context by an introductory chapter written by Professor Brian Caddy examining the future of forensic science. • A key text that traces the historical development of forensic science through reflective editorials published in the journal Science and Justice, and the Journal of the Forensic Science Society • Includes introductory chapter by Professor Brian Caddy • Divided into themed sections to reflect current commentary and debate