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Inferential Statisticshard
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Suppose we are testing H0:θ=θ0H_0: \theta = \theta_0H0​:θ=θ0​ against H1:θ≠θ0H_1: \theta \neq \theta_0H1​:θ=θ0​ using the Likelihood Ratio Test. If Λ=L(θ0)L(θ^)\Lambda = \frac{L(\theta_0)}{L(\hat{\theta})}Λ=L(θ^)L(θ0​)​ is the likelihood ratio, which statement accurately describes the asymptotic behavior of the statistic T=−2ln⁡ΛT = -2 \ln \LambdaT=−2lnΛ as the sample size nnn tends to infinity?