Questions related to sufficient statistics and confidence interval

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A sufficient statistic for θ in the context of a normal distribution N(μ,θ) is derived using the factorization criterion, focusing on the sample variance. The maximum likelihood estimator of θ is calculated as (1/n)Σ(Xi-μ)². To construct a confidence interval for θ, one can utilize the chi-squared distribution, noting that Σ(Xi-μ)²/θ follows a chi-squared distribution with n degrees of freedom. By finding critical values a and b from the chi-squared table, the probability statement can be transformed to express confidence intervals for θ. This approach effectively combines sufficient statistics and maximum likelihood estimation to derive confidence intervals.
StudentW
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Homework Statement


Suppose X1, X2, ..., Xn constitute a random sample from a population following N(μ,θ) where μ is known.

(a)Find a sufficient statistic for θ.
(b)Use the maximum likelihood estimator of θ to construct a confidence interval for θ with confidence level 1-α.

Homework Equations


The Attempt at a Solution


For part (a), I have tried to use the factorization criterion to find the sufficient statistic for θ but I have difficulty in separating θ from the exponential function as θ is the denominator. Can someone teach me how to get a function that depends on Xi only!

For part (b), the maximum likelihood estimator of θ is (1/n)*Σ(Xi-μ)^2. I am not sure about whether the information that Σ(Xi-μ)^2/θ follows chi square distribution with n degrees of freedom can help us to find the confidence interval! Can someone teach me how to get the confidence interval as well?
 
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StudentW said:

Homework Statement


Suppose X1, X2, ..., Xn constitute a random sample from a population following N(μ,θ) where μ is known.

(a)Find a sufficient statistic for θ.
(b)Use the maximum likelihood estimator of θ to construct a confidence interval for θ with confidence level 1-α.

Homework Equations


The Attempt at a Solution


For part (a), I have tried to use the factorization criterion to find the sufficient statistic for θ but I have difficulty in separating θ from the exponential function as θ is the denominator. Can someone teach me how to get a function that depends on Xi only!

For part (b), the maximum likelihood estimator of θ is (1/n)*Σ(Xi-μ)^2. I am not sure about whether the information that Σ(Xi-μ)^2/θ follows chi square distribution with n degrees of freedom can help us to find the confidence interval! Can someone teach me how to get the confidence interval as well?

Use a chi-squared table to find points ##a## and ##b## such that
P(\chi^2(n) \leq a) = \frac{\alpha}{2}, \; P(\chi^2(n) \geq b) = \frac{\alpha}{2}
Thus
P\left( a \leq \frac{\sum(X_i - \mu)^2}{\theta} \leq b \right) = 1 - \alpha.
Now turn that into a ##1-\alpha## probability statement about ##\theta##.
 

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