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Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.
5
votes
Bayes' Theorem and Agresti-Coull: Will it blend?
When applying the formula for P(B|A) for Agresti-Coull, it seems important to me to use, for the denominator (ñ), a number with uncertainty. The formula ñ=P(A)*N+4 (where N is the size of your sample …