Lindley's paradox refers to a phenomenon in Bayesian statistics that highlights a contradiction between intuitive decision-making and the results produced by Bayesian analysis. Named after the statistician David Lindley, the paradox occurs when the Bayesian approach yields a conclusion that seems counterintuitive, especially in the context of hypothesis testing. The paradox typically involves a scenario where there are two competing hypotheses about a situation. An intuitive analysis may suggest that one hypothesis is significantly more likely than the other based on prior belief or evidence.
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