Statistical Analysis in Forensic Science (PDF)

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.