Autore	Bozza Silvia
Edizione	[1st ed. 2022.]
Pubbl/distr/stampa	Cham, : Springer Nature, 2022
Descrizione fisica	1 online resource (XII, 187 p. 22 illus., 5 illus. in color.)
Disciplina	519.5
Collana	Springer Texts in Statistics
Soggetto topico	Statistics Mathematical statistics—Data processing Forensic sciences Medical jurisprudence Forensic psychology Social sciences—Statistical methods Statistical Theory and Methods Statistics and Computing Forensic Science Forensic Medicine Forensic Psychology Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Estadística bayesiana Processament de dades Criminalística R (Llenguatge de programació)
Soggetto genere / forma	Llibres electrònics
Soggetto non controllato	Bayes factor scientific evidence decision making forensic science uncertainty management probability theory forensic decision analysis Bayesian modeling R Bayesian statistics probabilistic inference
ISBN	3-031-09839-0
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Chapter 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.
Record Nr.	UNISA-996495166503316

Pubbl/distr/stampa	[Place of publication not identified], : Wiley, 2006
Disciplina	363.2501/519542
Collana	Statistics in practice Bayesian networks and probabilistic inference in forensic science
Soggetto topico	Bayesian statistical decision theory - Graphic methods Uncertainty (Information theory) - Graphic methods Forensic sciences - Graphic methods Mathematical Statistics Mathematics Physical Sciences & Mathematics
ISBN	0-470-09175-4 0-470-09174-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	The logic of uncertainty -- The logic of Bayesian networks -- Evaluation of scientific evidence -- Bayesian networks for evaluating scientific evidence -- DNA evidence -- Transfer evidence -- Aspects of the combination of evidence -- Pre-assessment -- Qualitative and sensitivity analyses -- Continuous networks -- Further applications.
Record Nr.	UNINA-9910144723503321

Edizione	[2nd ed.]
Pubbl/distr/stampa	Chichester, England : , : Wiley, , 2014
Descrizione fisica	1 online resource (473 p.)
Disciplina	363.2501/519542
Collana	Statistics in Practice
Soggetto topico	Bayesian statistical decision theory - Graphic methods Uncertainty (Information theory) - Graphic methods Forensic sciences - Graphic methods
ISBN	1-118-91476-7 1-118-91475-9
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Cover; Title Page; Copyright; Contents; Foreword; Preface to the second edition; Preface to the first edition; Chapter 1 The logic of decision; 1.1 Uncertainty and probability; 1.1.1 Probability is not about numbers, it is about coherent reasoning under uncertainty; 1.1.2 The first two laws of probability; 1.1.3 Relevance and independence; 1.1.4 The third law of probability; 1.1.5 Extension of the conversation; 1.1.6 Bayes' theorem; 1.1.7 Probability trees; 1.1.8 Likelihood and probability; 1.1.9 The calculus of (probable) truths; 1.2 Reasoning under uncertainty 1.2.1 The Hound of the Baskervilles1.2.2 Combination of background information and evidence; 1.2.3 The odds form of Bayes' theorem; 1.2.4 Combination of evidence; 1.2.5 Reasoning with total evidence; 1.2.6 Reasoning with uncertain evidence; 1.3 Population proportions, probabilities and induction; 1.3.1 The statistical syllogism; 1.3.2 Expectations and population proportions; 1.3.3 Probabilistic explanations; 1.3.4 Abduction and inference to the best explanation; 1.3.5 Induction the Bayesian way; 1.4 Decision making under uncertainty; 1.4.1 Bookmakers in the Courtrooms?; 1.4.2 Utility theory 1.4.3 The rule of maximizing expected utility1.4.4 The loss function; 1.4.5 Decision trees; 1.4.6 The expected value of information; 1.5 Further readings; Chapter 2 The logic of Bayesian networks and influence diagrams; 2.1 Reasoning with graphical models; 2.1.1 Beyond detective stories; 2.1.2 Bayesian networks; 2.1.3 A graphical model for relevance; 2.1.4 Conditional independence; 2.1.5 Graphical models for conditional independence: d-separation; 2.1.6 A decision rule for conditional independence; 2.1.7 Networks for evidential reasoning; 2.1.8 The Markov property; 2.1.9 Influence diagrams 2.1.10 Conditional independence in influence diagrams2.1.11 Relevance and causality; 2.1.12 The Hound of the Baskervilles revisited; 2.2 Reasoning with Bayesian networks and influence diagrams; 2.2.1 Divide and conquer; 2.2.2 From directed to triangulated graphs; 2.2.3 From triangulated graphs to junction trees; 2.2.4 Solving influence diagrams; 2.2.5 Object-oriented Bayesian networks; 2.2.6 Solving object-oriented Bayesian networks; 2.3 Further readings; 2.3.1 General; 2.3.2 Bayesian networks and their predecessors in judicial contexts Chapter 3 Evaluation of scientific findings in forensic science3.1 Introduction; 3.2 The value of scientific findings; 3.3 Principles of forensic evaluation and relevant propositions; 3.3.1 Source level propositions; 3.3.1.1 Notation; 3.3.1.2 Single stain; 3.3.2 Activity level propositions; 3.3.2.1 Notation and formulaic development; 3.3.3 Crime level propositions; 3.3.3.1 Notation; 3.3.3.2 Association propositions; 3.3.3.3 Intermediate association propositions; 3.4 Pre-assessment of the case; 3.5 Evaluation using graphical models; 3.5.1 Introduction 3.5.2 General aspects of the construction of Bayesian networks
Record Nr.	UNINA-9910132177003321

Pubbl/distr/stampa	Chichester, : John Wiley and Sons, 2010
Descrizione fisica	1 online resource (389 p.)
Disciplina	363.2501/519542
Altri autori (Persone)	TaroniFranco
Collana	Statistics in practice
Soggetto topico	Forensic sciences - Statistical methods Bayesian statistical decision theory
ISBN	1-282-54840-9 9786612548406 0-470-66508-4 0-470-66507-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Data Analysis in Forensic Science; Contents; Foreword; Preface; I The Foundations of Inference and Decision in Forensic Science; 1 Introduction; 1.1 The Inevitability of Uncertainty; 1.2 Desiderata in Evidential Assessment; 1.3 The Importance of the Propositional Framework and the Nature of Evidential Assessment; 1.4 From Desiderata to Applications; 1.5 The Bayesian Core of Forensic Science; 1.6 Structure of the Book; 2 Scientific Reasoning and Decision Making; 2.1 Coherent Reasoning Under Uncertainty; 2.1.1 A rational betting policy; 2.1.2 A rational policy for combining degrees of belief 2.1.3 A rational policy for changing degrees of belief2.2 Coherent Decision Making Under Uncertainty; 2.2.1 A method for measuring the value of consequences; 2.2.2 The consequences of rational preferences; 2.2.3 Intermezzo: some more thoughts about rational preferences; 2.2.4 The implementation of coherent decision making under uncertainty: Bayesian networks; 2.2.5 The connection between pragmatic and epistemic standards of reasoning; 2.3 Scientific Reasoning as Coherent Decision Making; 2.3.1 Bayes' theorem; 2.3.2 The theories' race; 2.3.3 Statistical reasoning: the models' race 2.3.4 Probabilistic model building: betting on random quantities2.4 Forensic Reasoning as Coherent Decision Making; 2.4.1 Likelihood ratios and the 'weight of evidence'; 2.4.2 The expected value of information; 2.4.3 The hypotheses' race in the law; 3 Concepts of Statistical Science and Decision Theory; 3.1 Random Variables and Distribution Functions; 3.1.1 Univariate random variables; 3.1.2 Measures of location and variability; 3.1.3 Multiple random variables; 3.2 Statistical Inference and Decision Theory; 3.2.1 Utility theory; 3.2.2 Maximizing expected utility; 3.2.3 The loss function 3.3 The Bayesian Paradigm3.3.1 Sequential use of Bayes' theorem; 3.3.2 Principles of rational inference in statistics; 3.3.3 Prior distributions; 3.3.4 Predictive distributions; 3.3.5 Markov Chain Monte Carlo methods (MCMC); 3.4 Bayesian Decision Theory; 3.4.1 Optimal decisions; 3.4.2 Standard loss functions; 3.5 R Code; II Forensic Data Analysis; 4 Point Estimation; 4.1 Introduction; 4.2 Bayesian Decision for a Proportion; 4.2.1 Estimation when there are zero occurrences in a sample; 4.2.2 Prior probabilities; 4.2.3 Prediction 4.2.4 Inference for 0 in the presence of background data on the number of successes4.2.5 Multinomial variables; 4.3 Bayesian Decision for a Poisson Mean; 4.3.1 Inference about the Poisson parameter in the absence of background events; 4.3.2 Inference about the Poisson parameter in the presence of background events; 4.3.3 Forensic inference using graphical models; 4.4 Bayesian Decision for Normal Mean; 4.4.1 Case with known variance; 4.4.2 Case with unknown variance; 4.4.3 Estimation of the mean in the presence of background data; 4.5 R Code; 5 Credible Intervals; 5.1 Introduction 5.2 Credible Intervals and Lower Bounds
Record Nr.	UNINA-9910140587703321

Autore	Alex Biedermann
Pubbl/distr/stampa	Frontiers Media SA, 2014
Descrizione fisica	1 online resource (39 pages)
Collana	Frontiers Research Topics
Soggetto topico	Biology - General Biology Health & Biological Sciences
Soggetto non controllato	probability theory interpretation Bacterial DNA Statistics and the law Forensic DNA profiling Low-template DNA analysis Commercialization DNA transfer forensic molecular biology
ISBN	9782889192502 (ebook)
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910131531203321