Könyv Statistical Analysis in Forensic Science - Evidential Value of Multivariate Physicochemical Data Grzegorz Zadora

Statistical Analysis in Forensic Science - Evidential Value of Multivariate Physicochemical Data

Szerző: Grzegorz Zadora
Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Beszállítói készleten
Küldés 10-18 napon belül
34 162 Ft
A practical guide for determining the evidential value of physicochemical data§Microtraces of variou...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2014
oldal
336
EAN
9780470972106
ISBN
0470972106
Enbook ID
02299802
Súly
662
Méretek
170 x 251 x 21

Teljes leírás

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.

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