Bayesian hypothesis testing is a statistical method that uses Bayes' theorem to update the probability of a hypothesis as more evidence or data becomes available. This approach allows for the incorporation of prior beliefs or information about a hypothesis, resulting in a posterior probability that reflects both the prior knowledge and the new data. It provides a flexible framework for decision-making under uncertainty, contrasting with traditional methods that rely on fixed significance levels.
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