: Discriminating between general propositions when no specific person or object of interest is available (e.g., general source characteristics).
: Introduction to Bayes' theorem as the standard for managing scientific uncertainty. Investigation vs. Evaluation : Bayes Factors for Forensic Decision Analyses wi...
: Providing real-world forensic examples and complete R sample code for sensitivity analyses and result interpretation. Key Concepts Covered Evaluation : : Providing real-world forensic examples and
: Moving beyond mere evaluation to coherent decision-making, helping scientists and legal professionals address practical questions under uncertainty. Bayes Factors for Forensic Decision Analyses wi...
: Practical guidance on standard models, including inferring proportions and normal means in forensic contexts. Audience and Accessibility Bayes Factors for Forensic Decision Analyses with R
Authored by , the text focuses on practical application over abstract theory, utilizing the R programming language to demonstrate computational techniques. Core Themes The content is structured around three primary pillars:
: Assessing findings relative to specific propositions (e.g., whether a trace came from a particular suspect).