Advanced Bayesian analysis using prevalence, sensitivity, and specificity.
Analysis Metrics
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Inference Results
16.10%
Positive Predictive Value (PPV)
The probability that a person has the condition given a positive test result.
Negative Predictive Value (NPV)99.95%
Total Positives5.90%
Population Simulation
True Pos
False Pos
False Neg
About this calculator
How Bayes' Theorem Works
Bayes' Theorem is used to calculate the 'posterior' probability—our confidence in a condition after seeing new evidence. In a medical context, even with a highly accurate test, the probability of actually having a rare disease after testing positive is surprisingly small if the prevalence in the general population is low.
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Pro Tips
Sensitivity is the test's ability to correctly identify positive cases.
Specificity is the test's ability to correctly identify negative cases.
Prevalence is the percentage of the population that actually has the condition.
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Fun Facts
"In 1917, Bayesian methods were used to find submarines."
"A test with 90% sensitivity and 90% specificity for a disease with 1% prevalence results in a positive predictive value of only about 8%."
"Alan Turing used a form of Bayesian inference to crack the German Enigma code during WWII."
