Introduction To Data Analysis With R For Forensic Scientists
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Introduction to Data Analysis with R for Forensic Scientists
Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed. However, many researchers lack the statistical skills or resources that would allow them to explore their data to its full potential. Introduction to Data Analysis with R for Forensic Sciences minimizes theory and mathematics and focus
Statistical 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.
Advanced Topics in Forensic DNA Typing: Interpretation
Advanced Topics in Forensic DNA Typing: Interpretation builds upon the previous two editions of John Butler's internationally acclaimed Forensic DNA Typing textbook with forensic DNA analysts as its primary audience. Intended as a third-edition companion to the Fundamentals of Forensic DNA Typing volume published in 2010 and Advanced Topics in Forensic DNA Typing: Methodology published in 2012, this book contains 16 chapters with 4 appendices providing up-to-date coverage of essential topics in this important field. Over 80 % of the content of this book is new compared to previous editions. - Provides forensic DNA analysts coverage of the crucial topic of DNA mixture interpretation and statistical analysis of DNA evidence - Worked mixture examples illustrate the impact of different statistical approaches for reporting results - Includes allele frequencies for 24 commonly used autosomal STR loci, the revised Quality Assurance Standards which went into effect September 2011