Bayesian Pitfalls in Resurrection Apologetics

Toward Priors, Likelihoods, and Dependence Corrections That Withstand Scrutiny Recent apologetic literature deploys Bayesian frameworks to argue that Jesus's resurrection is the most probable explanation of the Gospel data. This paper advances the thesis that these applications systematically mis-specify priors, suppress naturalistic alternatives, conflate testimonial sincerity with event truth, treat dependent sources as if independent, and illicitly transfer credibility from mundane details to miracle claims. Using the odds form of Bayes's theorem and standard corrections for specificity and dependence, we show that posteriors advertised as high-confidence are artifacts of input design rather than robust inferences. A corrected analysis-incorporating base-rate scarcity for miracle types, probability reserves for unknown mechanisms, and sensitivity checks-yields posterior probabilities that remain negligible. The broader lesson is methodological: properly used, Bayes enforces caution, transparency, and humility in historical inference rather than warrant for extraordinary conclusions.