1. A random sample of n = 20 products are taken from the production lines of a factory. Let = 1,..., 20, IID Xi Bernoulli(p) be the indicator of whether the i-th product defective for i where Р denotes the proportion of defective products in the population. It is desirable to test whether the the proportion of defective products is below 30%. (a) State the null hypothesis Ho and the alternative hypothesis Ha. (b) Describe the events of Type I error and Type II error in the procedure of making statistical decisions. 20 (c) Let T i=1 ₁X₁ denote the number of defective items in the sample. Suppose that we decide to reject Hỏ if T ≤ 4. Let π(p) denote the corresponding power function, i.e., π(p) = Pr (T ≤ 4|p). Determine the value of (p) at the points p = 0, 0.1, 0.2, 0.3,..., 0.9, and 1.0 and sketch the power function. (Hint: Use the statistical table for Binomial distribution.) = (d) What is the size of the test procedure in part (c), i.e., the maximum probability of making Type I error? (e) What is the power of the test procedure in part (c) when p = 0.1? (Hint: Both part (d) and part (e) can be obtained immediately from the power function (p).)
1. A random sample of n = 20 products are taken from the production lines of a factory. Let = 1,..., 20, IID Xi Bernoulli(p) be the indicator of whether the i-th product defective for i where Р denotes the proportion of defective products in the population. It is desirable to test whether the the proportion of defective products is below 30%. (a) State the null hypothesis Ho and the alternative hypothesis Ha. (b) Describe the events of Type I error and Type II error in the procedure of making statistical decisions. 20 (c) Let T i=1 ₁X₁ denote the number of defective items in the sample. Suppose that we decide to reject Hỏ if T ≤ 4. Let π(p) denote the corresponding power function, i.e., π(p) = Pr (T ≤ 4|p). Determine the value of (p) at the points p = 0, 0.1, 0.2, 0.3,..., 0.9, and 1.0 and sketch the power function. (Hint: Use the statistical table for Binomial distribution.) = (d) What is the size of the test procedure in part (c), i.e., the maximum probability of making Type I error? (e) What is the power of the test procedure in part (c) when p = 0.1? (Hint: Both part (d) and part (e) can be obtained immediately from the power function (p).)
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![1. A random sample of \( n = 20 \) products are taken from the production lines of a factory. Let \( X_i \overset{\text{IID}}{\sim} \text{Bernoulli}(p) \) be the indicator of whether the \( i \)-th product is defective for \( i = 1, \ldots, 20 \), where \( p \) denotes the proportion of defective products in the population. It is desirable to test whether the proportion of defective products is below 30%.
(a) State the null hypothesis \( H_0 \) and the alternative hypothesis \( H_a \).
(b) Describe the events of Type I error and Type II error in the procedure of making statistical decisions.
(c) Let \( T = \sum_{i=1}^{20} X_i \) denote the number of defective items in the sample. Suppose that we decide to reject \( H_0 \) if \( T \leq 4 \). Let \( \pi(p) \) denote the corresponding power function, i.e.,
\[
\pi(p) = \Pr(T \leq 4 \mid p).
\]
Determine the value of \( \pi(p) \) at the points \( p = 0, 0.1, 0.2, 0.3, \ldots, 0.9, \) and 1.0 and sketch the power function. (Hint: Use the statistical table for Binomial distribution.)
(d) What is the size of the test procedure in part (c), i.e., the maximum probability of making a Type I error?
(e) What is the power of the test procedure in part (c) when \( p = 0.1 \)? (Hint: Both part (d) and part (e) can be obtained immediately from the power function \( \pi(p) \).)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc58b2eee-5b79-4c9d-923b-d4e913d44dbe%2Fb11b2d77-f356-445b-a6a9-ad94b867dd12%2Fwhq02vi_processed.png&w=3840&q=75)
Transcribed Image Text:1. A random sample of \( n = 20 \) products are taken from the production lines of a factory. Let \( X_i \overset{\text{IID}}{\sim} \text{Bernoulli}(p) \) be the indicator of whether the \( i \)-th product is defective for \( i = 1, \ldots, 20 \), where \( p \) denotes the proportion of defective products in the population. It is desirable to test whether the proportion of defective products is below 30%.
(a) State the null hypothesis \( H_0 \) and the alternative hypothesis \( H_a \).
(b) Describe the events of Type I error and Type II error in the procedure of making statistical decisions.
(c) Let \( T = \sum_{i=1}^{20} X_i \) denote the number of defective items in the sample. Suppose that we decide to reject \( H_0 \) if \( T \leq 4 \). Let \( \pi(p) \) denote the corresponding power function, i.e.,
\[
\pi(p) = \Pr(T \leq 4 \mid p).
\]
Determine the value of \( \pi(p) \) at the points \( p = 0, 0.1, 0.2, 0.3, \ldots, 0.9, \) and 1.0 and sketch the power function. (Hint: Use the statistical table for Binomial distribution.)
(d) What is the size of the test procedure in part (c), i.e., the maximum probability of making a Type I error?
(e) What is the power of the test procedure in part (c) when \( p = 0.1 \)? (Hint: Both part (d) and part (e) can be obtained immediately from the power function \( \pi(p) \).)
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