Quick guide
How to use this calculator
- Enter the observations, probabilities, model parameters, or summary statistics requested by the visible labels.
- Keep every value on the same scale and confirm that the selected sampling relationship, distribution, and tail convention match the question you are investigating.
- Read the result together with its assumptions and interpretation. Statistical output summarizes uncertainty under a model; it does not repair biased data or establish causation.
Calculation method
How the bayes’ theorem calculator works
P(A|B)=P(B|A)P(A)/[P(B|A)P(A)+P(B|not A)P(not A)].
A strong test result can still imply a modest posterior when the prior event is rare.
Worked example
Bayes’ Theorem example
A 1% prior, 90% sensitivity, and 5% false-positive probability give a posterior of about 15.38%.
P(A|B)=P(B|A)P(A)/[P(B|A)P(A)+P(B|not A)P(not A)].
Supported inputs
Precision and limits
Model and design
Inputs must describe the same population and evidence definition; this arithmetic is not a medical diagnosis.
Numerical scope
Inputs use double-precision numerical methods with guarded domains. Datasets accept up to 10,000 finite plain-decimal values. Extremely large parameters or probabilities deep in a numerical tail may require specialist statistical software.
Interpretation
A strong test result can still imply a modest posterior when the prior event is rare.
Decision boundary
The calculator does not validate how data were collected, diagnose dependence or bias, choose a scientifically meaningful effect, or replace review by a qualified statistician for consequential research, medical, regulatory, safety, or policy decisions.
Privacy
Entered values and calculated results stay in this browser and are not sent to an analytics service.
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