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.