{"product_id":"bayes-factors-for-forensic-decision-analyses-with-r-hardcover","title":"Bayes Factors for Forensic Decision Analyses with R - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eSilvia Bozza\u003c\/b\u003e (Author), \u003cb\u003eFranco Taroni\u003c\/b\u003e (Author), \u003cb\u003eAlex Biedermann\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eBayes Factors for Forensic Decision Analyses with R\u003c\/i\u003e 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: \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e\u003cli\u003eProbabilistic 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.\u003c\/li\u003e\u003c\/ul\u003e\u003cul\u003e\u003cli\u003eDecision 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.\u003c\/li\u003e\u003c\/ul\u003e\u003cul\u003e\u003cli\u003eOperational 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.\u003c\/li\u003e\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eOver 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.\u003c\/p\u003e\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003eThis book is Open Access.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eBayes 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: \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e\u003cli\u003eProbabilistic 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.\u003c\/li\u003e\u003c\/ul\u003e\u003cul\u003e\u003cli\u003eDecision 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.\u003c\/li\u003e\u003c\/ul\u003e\u003cul\u003e\u003cli\u003eOperational 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.\u003c\/li\u003e\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eOver 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.\u003c\/p\u003e\u003cp\u003eThis 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.\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eThis book is Open Access.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003cb\u003eSilvia Bozza\u003c\/b\u003e is Associate Professor of Statistics at Ca' Foscari University of Venice (Italy), Department of Economics and Senior Researcher at the University of Lausanne (School of Criminal Justice). Her research interests are mainly focused on Bayesian modelling, decision theory and probabilistic graphical models with applications in forensic science. \u003cb\u003e\u003cbr\u003e\u003c\/b\u003e\u003cb\u003eFranco Taroni\u003c\/b\u003e is Full Professor of Forensic Statistics at the Faculty of Law, Criminal Justice and Public Administration, School of Criminal Justice, of the University of Lausanne (Switzerland). He publishes extensively in the area of probabilistic reasoning, decision making and data analysis in forensic science.\u003cbr\u003e\u003cb\u003eAlex Biedermann\u003c\/b\u003e is Associate Professor at the Faculty of Law, Criminal Justice and Public Administration, School of Criminal Justice, of the University of Lausanne (Switzerland). He researches and teaches in the area of evidential reasoning and decision making at the intersection between forensic science and the law. His work is multidisciplinary and pertains to forensic science, law and topics in probability and decision theory.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 187\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.5 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e November 01, 2022\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52239446606098,"sku":"9783031098383","price":97.18,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0941\/2211\/5346\/files\/VFBzYkxqL3NwRjh6bTJSeHZ5V3RyZz09.webp?v=1777879262","url":"https:\/\/ckbookstore.net\/products\/bayes-factors-for-forensic-decision-analyses-with-r-hardcover","provider":"CK BOOKSTORE","version":"1.0","type":"link"}