Introduction to the Bayes Factor and Decision Analysis

Abstract

AbstractThis chapter presents an overview of statistics in forensic science, with an emphasis on the Bayesian perspective and the role of the Bayes factor in logical inference and decision. The chapter introduces the reader to three key topics that forensic scientists commonly encounter and that are treated in this book: model choice, evaluation and investigation. For each of these themes, Bayes factors will be developed in later chapters and discussed using practical examples. Particular attention will be given to the distinction between feature- and score-based Bayes factors, representing different approaches to deal with input information (i.e., measurements). This introductory chapter also provides theoretical background that analysts might need during data analysis, including elements of forensic interpretation, computational methods, decision theory, prior elicitation and sensitivity analysis.