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Inferential Statisticshard
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Under the assumption of the Neyman-Pearson Lemma, for a simple hypothesis test H0:θ=θ0H_0: \theta=\theta_0H0​:θ=θ0​ vs H1:θ=θ1H_1: \theta=\theta_1H1​:θ=θ1​, if the likelihood ratio Λ(x)=L(θ0∣x)/L(θ1∣x)\Lambda(x) = L(\theta_0|x)/L(\theta_1|x)Λ(x)=L(θ0​∣x)/L(θ1​∣x) is a strictly monotonic function of a sufficient statistic T(x)T(x)T(x), what can be said about the rejection region?