LEADER 06138nam 22010335 450 001 9910623993803321 005 20240430175416.0 010 $a3-031-09839-0 024 7 $a10.1007/978-3-031-09839-0 035 $a(CKB)5600000000521464 035 $a(DE-He213)978-3-031-09839-0 035 $a(MiAaPQ)EBC7129909 035 $a(Au-PeEL)EBL7129909 035 $a(OCoLC)1349339889 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/93947 035 $a(PPN)265856469 035 $a(EXLCZ)995600000000521464 100 $a20221031d2022 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBayes Factors for Forensic Decision Analyses with R /$fby Silvia Bozza, Franco Taroni, Alex Biedermann 205 $a1st ed. 2022. 210 $aCham$cSpringer Nature$d2022 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (XII, 187 p. 22 illus., 5 illus. in color.) 225 1 $aSpringer Texts in Statistics,$x2197-4136 311 $a3-031-09838-2 327 $aChapter 1: Introduction to the Bayes factor and decision analysis -- Chapter 2: Bayes factor for model choice -- Chapter 3: Bayes factor for evaluative purposes -- Chapter 4: Bayes factor for investigative purposes. 330 $aBayes 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. 410 0$aSpringer Texts in Statistics,$x2197-4136 606 $aStatistics 606 $aMathematical statistics?Data processing 606 $aForensic sciences 606 $aMedical jurisprudence 606 $aForensic psychology 606 $aSocial sciences?Statistical methods 606 $aStatistical Theory and Methods 606 $aStatistics and Computing 606 $aForensic Science 606 $aForensic Medicine 606 $aForensic Psychology 606 $aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy 606 $aEstadística bayesiana$2thub 606 $aProcessament de dades$2thub 606 $aCriminalística$2thub 606 $aR (Llenguatge de programació)$2thub 608 $aLlibres electrònics$2thub 610 $aBayes factor 610 $ascientific evidence 610 $adecision making 610 $aforensic science 610 $auncertainty management 610 $aprobability theory 610 $aforensic 610 $adecision analysis 610 $aBayesian modeling 610 $aR 610 $aBayesian statistics 610 $aprobabilistic inference 615 0$aStatistics. 615 0$aMathematical statistics?Data processing. 615 0$aForensic sciences. 615 0$aMedical jurisprudence. 615 0$aForensic psychology. 615 0$aSocial sciences?Statistical methods. 615 14$aStatistical Theory and Methods. 615 24$aStatistics and Computing. 615 24$aForensic Science. 615 24$aForensic Medicine. 615 24$aForensic Psychology. 615 24$aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy. 615 7$aEstadística bayesiana 615 7$aProcessament de dades 615 7$aCriminalística 615 7$aR (Llenguatge de programació) 676 $a519.5 700 $aBozza$b Silvia$4aut$4http://id.loc.gov/vocabulary/relators/aut$01271641 702 $aTaroni$b Franco$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aBiedermann$b Alex$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910623993803321 996 $aBayes Factors for Forensic Decision Analyses with R$92995623 997 $aUNINA