Bayes' Theorem Visualizer

P(H|E) = P(E|H)·P(H) / P(E) — update beliefs with evidence

P(H) — Prior
P(H̄)
P(E|H) true positive
P(E|H̄) false positive
P(H|E) posterior

Scenarios

Parameters

P(H|E) — Posterior
P(H|E) = P(E|H) × P(H)
──────────────────────
P(E|H)·P(H) + P(E|H̄)·P(H̄)
Base rate fallacy: Even a 99% accurate test for a 1% disease gives only ~17% posterior probability — most positives are false!

P(E) = P(E|H)P(H) + P(E|H̄)P(H̄)

The area diagram shows exactly which fraction of the "positive evidence" box comes from true vs. false positives.