Enter the prior probability, likelihood, and evidence into the calculator to determine the posterior probability using Bayes’ theorem.
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Bayesian Calculation Formula
The following formula is used to calculate the posterior probability using Bayes’ theorem:
P(H|E) = [P(E|H) * P(H)] / P(E)
Variables:
- P(H|E) is the posterior probability, the probability of the hypothesis after seeing the evidence.
- P(E|H) is the likelihood, the probability of the evidence given that the hypothesis is true.
- P(H) is the prior probability, the initial probability of the hypothesis before seeing the evidence.
- P(E) is the evidence, the total probability of the evidence.
To calculate the posterior probability, multiply the likelihood by the prior probability, then divide by the evidence.
What is Bayesian Calculation?
Bayesian calculation involves updating the probability estimate for a hypothesis as additional evidence is acquired. It is a fundamental concept in Bayesian statistics, which provides a mathematical framework for incorporating new evidence to revise existing beliefs or hypotheses.
How to Calculate Posterior Probability?
The following steps outline how to calculate the posterior probability using Bayes’ theorem:
- First, determine the prior probability (P(H)) based on existing knowledge or historical data.
- Next, determine the likelihood (P(E|H)), which is the probability of observing the evidence assuming the hypothesis is true.
- Then, determine the evidence (P