: Providing real-world forensic examples and complete R sample code for sensitivity analyses and result interpretation. Key Concepts Covered
: Introduction to Bayes' theorem as the standard for managing scientific uncertainty. Investigation vs. Evaluation : Bayes Factors for Forensic Decision Analyses wi...
The book (published in 2022) provides a comprehensive introduction to using Bayesian methods—specifically Bayes factors —to evaluate scientific evidence and support rational decision-making in forensic science. : Providing real-world forensic examples and complete R
: Discriminating between general propositions when no specific person or object of interest is available (e.g., general source characteristics). Evaluation : The book (published in 2022) provides
: 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
: Using Bayes factors to quantify the "weight of evidence" by measuring the change from prior to posterior odds.
: The text introduces MCMC (Markov Chain Monte Carlo), importance sampling, and Chib's formula for calculating Bayes factors.