Interactive Tool
Bayes' Calculator
Enter the prior probability, the likelihood of your evidence given the hypothesis, and the overall probability of the evidence. Watch the posterior update step by step.
Enter three values as decimals between 0 and 1. For example, 0.01 means 1%, 0.95 means 95%. The calculator will show you the posterior probability — your updated belief after seeing the evidence.
Example: Medical Test
A disease affects 1% of the population (P(H) = 0.01). A test correctly catches 95% of sick people (P(E|H) = 0.95). But the test also falsely flags 5% of healthy people. So the overall chance of testing positive is: 0.01 × 0.95 + 0.99 × 0.05 = 0.059. Fill in the values above and click Calculate to see that a positive test only gives about a 16% chance of actually having the disease.