Bayes' theorem in the form that actually matters day to day: why a 99%-accurate test on a rare condition is still usually wrong, why doctors and juries fall for the same reasoning error, and how the same math runs underneath spam filters and alert triage. Priors, likelihoods, and posteriors made concrete with natural-frequency arithmetic instead of symbol-pushing.
Reasoning
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Bayes' Theorem for Engineers: The Base-Rate Trap That Fools Doctors, Juries, and Alert Dashboards