Find the bayesian estimator of micro that minimizes squared


Suppose for a sample of size n = 10, that X has a N(µ, 1) distribution, where µ is a randomvariable with prior distribution N(0, 1). It can be shown that the posterior distribution of µgiven X is N(θ, σ2
), where
θ =
X
1 + 1/n and σ
2 =
1/n
1 + 1/n
(a) Find the Bayesian estimator of µ that minimizes squared error loss.
(b) Find a 90% interval estimate of µ, given that X = 10.

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