5. Suppose that the observed data X~ f(x; 0). Then the likelihood function is L(0) = f(x; 0). An intuitive test for the simple hypothesis Ho: 0 = 0o and H₁ : 0 = 0₁, where 00 and 0₁ are given parameters, is the likelihood ratio test, which rejects Ho when L(01)/L(00) ≥c, for some constant c to be determined so that type I error is a. The test is also called the Neyman-Person test and its equivalent statistic A(x) = log(L(01)/L(00)) is called the log- likelihood ratio statistic. (a) Suppose X₁, Xn ~ii.d. N(μ,02) where o is known (for simplicity). Consider the testing problem Ho = 0 vs. H₁: = μ₁ where μ₁0. Derive the log-likelihood ratio statistic and shows that it is a monotonic function of sample mean X. (b) If X₁, Xn are a random sample from Bernoulli (p), derive the log-likelihood ratio statistic for Ho: p= po vs. H₁: p= P₁ where p₁>po and show that it is a monotonic function of p= n¹(X₁+...+Xn), the sample proportion.

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5. Suppose that the observed data X~ f(x; 0). Then the likelihood function is L(0) = f(x;0).
An intuitive test for the simple hypothesis Ho: 0 = 0o and H₁ : 0 = 0₁, where and 0₁ are
given parameters, is the likelihood ratio test, which rejects Ho when
L(01)/L(00) ≥c,
for some constant c to be determined so that type I error is a. The test is also called the
Neyman-Person test and its equivalent statistic X(x) = log(L(01)/L(00)) is called the log-
likelihood ratio statistic.
(a) Suppose X₁,..., Xn ~ii.d. N(μ,0²) where σ is known (for simplicity). Consider the
testing problem
Hoμ0 vs. H₁: = μ1
where μ₁ > 0. Derive the log-likelihood ratio statistic and shows that it is a monotonic
function of sample mean X.
(b) If X₁,
Xn are a random sample from Bernoulli (p), derive the log-likelihood ratio
"
statistic for
Ho p = po vs. H₁: p= P₁
where p₁>po and show that it is a monotonic function of p= n−¹(X₁ ++ Xn), the
sample proportion.
Transcribed Image Text:5. Suppose that the observed data X~ f(x; 0). Then the likelihood function is L(0) = f(x;0). An intuitive test for the simple hypothesis Ho: 0 = 0o and H₁ : 0 = 0₁, where and 0₁ are given parameters, is the likelihood ratio test, which rejects Ho when L(01)/L(00) ≥c, for some constant c to be determined so that type I error is a. The test is also called the Neyman-Person test and its equivalent statistic X(x) = log(L(01)/L(00)) is called the log- likelihood ratio statistic. (a) Suppose X₁,..., Xn ~ii.d. N(μ,0²) where σ is known (for simplicity). Consider the testing problem Hoμ0 vs. H₁: = μ1 where μ₁ > 0. Derive the log-likelihood ratio statistic and shows that it is a monotonic function of sample mean X. (b) If X₁, Xn are a random sample from Bernoulli (p), derive the log-likelihood ratio " statistic for Ho p = po vs. H₁: p= P₁ where p₁>po and show that it is a monotonic function of p= n−¹(X₁ ++ Xn), the sample proportion.
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