Bayesian hypothesis testing is a statistical method that evaluates competing hypotheses by updating the probability of each hypothesis based on new evidence or data. This approach incorporates prior beliefs about the hypotheses and combines them with the likelihood of observing the data given each hypothesis, leading to a posterior probability distribution. Unlike traditional methods, Bayesian testing allows for a more flexible interpretation of evidence and decision-making based on the probabilities derived from both prior knowledge and observed data.
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