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Data Analysis in Forensic Science
A Bayesian Decision Perspective
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Veröffentlicht 2010, von Franco Taroni, Silvia Bozza, Alex Biedermann, Paolo Garbolino, Colin Aitken bei John Wiley & Sons
ISBN: 978-0-470-66507-7
Auflage: 1. Auflage
Reihe: Statistics in Practice
388 Seiten
This is the first text to examine the use of statistical methods in
forensic science and bayesian statistics in combination.
The book is split into two parts: Part One concentrates on the
philosophies of statistical inference. Chapter One examines the
differences between the frequentist, the likelihood and the
Bayesian perspectives, before Chapter Two explores the Bayesian
decision-theoretic ...
forensic science and bayesian statistics in combination.
The book is split into two parts: Part One concentrates on the
philosophies of statistical inference. Chapter One examines the
differences between the frequentist, the likelihood and the
Bayesian perspectives, before Chapter Two explores the Bayesian
decision-theoretic ...
Beschreibung
This is the first text to examine the use of statistical methods in
forensic science and bayesian statistics in combination.
The book is split into two parts: Part One concentrates on the
philosophies of statistical inference. Chapter One examines the
differences between the frequentist, the likelihood and the
Bayesian perspectives, before Chapter Two explores the Bayesian
decision-theoretic perspective further, and looks at the benefits
it carries.
Part Two then introduces the reader to the practical aspects
involved: the application, interpretation, summary and presentation
of data analyses are all examined from a Bayesian
decision-theoretic perspective. A wide range of statistical
methods, essential in the analysis of forensic scientific data is
explored. These include the comparison of allele proportions in
populations, the comparison of means, the choice of sampling size,
and the discrimination of items of evidence of unknown origin into
predefined populations.
Throughout this practical appraisal there are a wide variety of
examples taken from the routine work of forensic scientists. These
applications are demonstrated in the ever-more popular R language.
The reader is taken through these applied examples in a
step-by-step approach, discussing the methods at each stage.
This is the first text to examine the use of statistical methods in
forensic science and bayesian statistics in combination.
The book is split into two parts: Part One concentrates on the
philosophies of statistical inference. Chapter One examines the
differences between the frequentist, the likelihood and the
Bayesian perspectives, before Chapter Two explores the Bayesian
decision-theoretic perspective further, and looks at the benefits
it carries.
Part Two then introduces the reader to the practical aspects
involved: the application, interpretation, summary and presentation
of data analyses are all examined from a Bayesian
decision-theoretic perspective. A wide range of statistical
methods, essential in the analysis of forensic scientific data is
explored. These include the comparison of allele proportions in
populations, the comparison of means, the choice of sampling size,
and the discrimination of items of evidence of unknown origin into
predefined populations.
Throughout this practical appraisal there are a wide variety of
examples taken from the routine work of forensic scientists. These
applications are demonstrated in the ever-more popular R language.
The reader is taken through these applied examples in a
step-by-step approach, discussing the methods at each stage.