Video narration
Could a positive test still leave you less likely than not to have the condition? Bayes' theorem is how you update your starting chance using what the test result tells you. The base rate-the condition's starting frequency-is just one person in a hundred. Imagine ten thousand people taking this hypothetical test. One hundred have the condition, and the test catches nine in ten of them: ninety true positives. That's different from the test falsely flagging one in twenty healthy people. Among the 9,900 healthy people, that creates 495 false positives. Now compare all positive results: ninety true positives against 495 false positives. There are 585 positives altogether, and only 90 are true. A positive result is evidence, not a verdict. Because the condition is rare, false positives outnumber true positives. So, yes: with these rates, a positive result means only about a 15 percent chance of having the condition.