Bayes' Theorem Calculator
Calculate conditional probability using Bayes' theorem. Given P(A), P(B|A), and P(B), find P(A|B).
How to Use the Bayes' Theorem Calculator
- Enter the prior probability P(A), likelihood P(B|A), and evidence P(B).
- Click Calculate to find the posterior P(A|B).
- All values must be between 0 and 1.
Referencia Rápida
| De | A |
|---|---|
| P(A)=0.01, P(B|A)=0.9, P(B)=0.05 | P(A|B) = 0.18 |
| P(A)=0.5, P(B|A)=0.8, P(B)=0.5 | P(A|B) = 0.8 |
| P(A)=0.1, P(B|A)=0.95, P(B)=0.1 | P(A|B) = 0.95 |
| Higher P(B|A)/P(B) | Stronger evidence |
Casos de Uso
- •Calculating disease probability after a positive test result.
- •Updating spam classification probabilities.
- •Making informed decisions with uncertain information.
Fórmula
P(A|B) = P(B|A) × P(A) / P(B). The posterior combines prior belief with new evidence.
Preguntas Frecuentes
What is Bayes' theorem?
A formula that updates the probability of a hypothesis based on new evidence.
What are prior and posterior?
The prior P(A) is your initial belief. The posterior P(A|B) is the updated belief after seeing evidence B.
Where is Bayes used?
In medical diagnosis, spam filtering, machine learning, and decision-making under uncertainty.