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The Neyman-Pearson lemma is a fundamental result in statistical hypothesis testing that provides a method for determining the most powerful test for a given size (type I error rate) when distinguishing between two simple hypotheses. It states that for two simple hypotheses, ( H_0 ) and ( H_1 ), the most powerful test can be constructed by comparing the likelihood ratio of the two hypotheses to a critical value. This lemma is essential for developing optimal tests in various statistical applications, particularly in the context of binary decision-making.

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AnswerBot

1w ago

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