Based on this information, complete the parts below. (a) What are the null hypothesis H and the alternative hypothesis H, that should be used for the test? Ho :O H₁:0 (b) Suppose that the managers decide not to reject the null hypothesis. What sort of error might they be making? (Choose one) (c) Suppose the true mean completion time for the assembly line operation is 38 minutes. Fill in the blanks to descr Type II error. A Type II error would be (Choose one) (Choose one) when, in fact, μ is (Choose one) the hypothesis that u is (Choose one)

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Author:Amos Gilat
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### Statistical Analysis of Assembly Line Completion Times

**Scenario:**
Managers at an automobile manufacturing plant want to examine the mean completion time, \( \mu \), of an assembly line operation. Previously, the mean completion time was 44 minutes, but the managers believe this may have changed. A statistical test is planned to verify this.

After selecting a random sample of assembly line completion times, the sample mean is calculated as 40 minutes. The standard deviation remains at 3 minutes, as previously reported.

**Task:**
Based on this scenario, complete the following parts:

#### (a) Hypotheses
- **Null Hypothesis (\( H_0 \)):**
  - Hypothesis statement placeholder: [ ]
- **Alternative Hypothesis (\( H_1 \)):**
  - Hypothesis statement placeholder: [ ]

#### (b) Type of Error
- **Suppose the managers decide not to reject the null hypothesis. What sort of error might they be making?**
  - \([ \text{Choose one} ]\)

#### (c) Type II Error
- **Suppose the true mean completion time for the assembly line operation is 38 minutes. Complete the blanks to describe a Type II error:**
  - A Type II error would be \([ \text{Choose one} ]\) the hypothesis that \( \mu \) is \([ \text{Choose one} ]\)
  - when, in fact, \( \mu \) is \([ \text{Choose one} ]\)

#### Diagram Overview
- The diagram provides symbols and inequality signs to fill in the hypotheses and error descriptions. These include:
  - \( \mu = \)
  - \( \mu < \)
  - \( \mu > \)
  - \( \mu \neq \)

This exercise is designed to help understand hypothesis testing and errors in statistical decision-making.
Transcribed Image Text:### Statistical Analysis of Assembly Line Completion Times **Scenario:** Managers at an automobile manufacturing plant want to examine the mean completion time, \( \mu \), of an assembly line operation. Previously, the mean completion time was 44 minutes, but the managers believe this may have changed. A statistical test is planned to verify this. After selecting a random sample of assembly line completion times, the sample mean is calculated as 40 minutes. The standard deviation remains at 3 minutes, as previously reported. **Task:** Based on this scenario, complete the following parts: #### (a) Hypotheses - **Null Hypothesis (\( H_0 \)):** - Hypothesis statement placeholder: [ ] - **Alternative Hypothesis (\( H_1 \)):** - Hypothesis statement placeholder: [ ] #### (b) Type of Error - **Suppose the managers decide not to reject the null hypothesis. What sort of error might they be making?** - \([ \text{Choose one} ]\) #### (c) Type II Error - **Suppose the true mean completion time for the assembly line operation is 38 minutes. Complete the blanks to describe a Type II error:** - A Type II error would be \([ \text{Choose one} ]\) the hypothesis that \( \mu \) is \([ \text{Choose one} ]\) - when, in fact, \( \mu \) is \([ \text{Choose one} ]\) #### Diagram Overview - The diagram provides symbols and inequality signs to fill in the hypotheses and error descriptions. These include: - \( \mu = \) - \( \mu < \) - \( \mu > \) - \( \mu \neq \) This exercise is designed to help understand hypothesis testing and errors in statistical decision-making.
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