The first edition of Statistics and the Evaluation of Evidence for Forensic Scientists established itself as a highly regarded authority on this area. Fully revised and updated, the second edition provides significant new material on areas of current interest including:
* Glass Interpretation
* Fibres Interpretation
* Bayes' Nets
The title presents comprehensive coverage of the statistical evaluation of forensic evidence. It is written with the assumption of a modest mathematical background and is illustrated throughout with up-to-date examples from a forensic science background.
The clarity of exposition makes this book ideal for all forensic scientists, lawyers and other professionals in related fields interested in the quantitative assessment and evaluation of evidence.
'There can be no doubt that the appreciation of some evidence in a court of law has been greatly enhanced by the sound use of statistical ideas and one can be confident that the next decade will see further developments, during which time this book will admirably serve those who have cause to use statistics in forensic science.'
D.V. Lindley
Rezensionen / Stimmen
"...wholly admirable...the benefits of using sensible notation to understand how to combine different types of evidence shine through." (Significance - magazine of the Royal Statistical Society, March 2005) "We wish to congratulate Profs Aitken and Taroni on their scholarly and valuable contribution to the field." (Law, Probability and Risk, 2006)
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Editions-Typ
Maße
Höhe: 23.5 cm
Breite: 16.6 cm
Dicke: 3.4 cm
Gewicht
ISBN-13
978-0-470-84367-3 (9780470843673)
Schweitzer Klassifikation
Colin Aitken, School of Mathematics, University of Edinburgh, UK.
Franco Taroni, Institute de Police Scientifique et de Criminologie, University of Lausanne, Switzerland.
Autor*in
Univ. of Edinburgh, UK
Univ. of Lausanne, Switzerland
Preface to the first edition.
Preface to the second edition.
Uncertainty in forensic science.
Variation.
The evaluation of evidence.
Historical review.
Bayesian inference.
Sampling.
Interpretation.
Transfer evidence.
Discrete data.
Continuous data.
Multivariate analysis.
Fibres.
DNA profiling.
Bayesian networks.
References.
Notation.
Cases.