Chapter 7: Q7.3-2E (page 402)
Show that in Example 7.3.2 it must be true that V ≤ 0.01 after 22 items have been selected. Also show that V > 0.01 until at least seven items have been selected.
Short Answer
Proved.
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Chapter 7: Q7.3-2E (page 402)
Show that in Example 7.3.2 it must be true that V ≤ 0.01 after 22 items have been selected. Also show that V > 0.01 until at least seven items have been selected.
Proved.
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Question: Suppose that \({\bf{X1, }}{\bf{. }}{\bf{. }}{\bf{. , Xn}}\)form a random sample froma normal distribution for which both the mean and thevariance are unknown. Find the M.L.E. of the 0.95 quantileof the distribution, that is, of the point \({\bf{\theta }}\) such that
\({\bf{Pr}}\left( {{\bf{X < \theta }}} \right){\bf{ = 0}}{\bf{.95}}\)
Suppose that the proportion θ of defective items in a large manufactured lot is known to be either 0.1 or 0.2, and the prior p.f. of \(\theta \) is as follows:
\(\xi \left( {0.1} \right) = 0.7\)and\(\xi \left( {0.2} \right) = 0.3\).
Suppose also that when eight items are selected at random from the lot, it is found that exactly two of them are defective. Determine the posterior p.f. of \(\theta \)
Show that the family of beta distributions is a conjugate
family of prior distributions for samples from a negative binomial distribution with a known value of the parameterrand an unknown value of the parameterp(0<p <1).
Suppose that a single observation X is to be taken from the uniform distribution on the interval \(\left[ {{\bf{\theta - }}\frac{{\bf{1}}}{{\bf{2}}}{\bf{,\theta + }}\frac{{\bf{1}}}{{\bf{2}}}} \right]\), the value of θ is unknown, and the prior distribution of θ is the uniform distribution on the interval [10, 20]. If the observed value of X is 12, what is the posterior distribution of θ?
Question: Consider the conditions of Exercise 2 again. Suppose that the prior distribution of θ is as given in Exercise 2, and suppose again that 20 items are selected at random from the shipment.
a. For what number of defective items in the sample will the mean squared error of the Bayes estimate be a maximum?
b. For what number the mean squared error of the Bayes estimate will be a minimum?
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