For the following information, determine whether a normal sampling distribution can be used, where p is the population proportion, a is the level of significance, p is the sample proportion, and n is the sample size. If it can be used, test the claim. Claim: p>0.67; a= 0.06. Sample statistics: p= 0.72, n = 325 Let q = 1-pand let q= 1-p. A normal sampling distribution V be used here, since V5 and V5. If a normal sampling distribution can be used, identify the hypotheses for testing the claim. Select the correct choice below and, if necessary, fill in the answer boxes to complete your choice. O A. Ho: p< Ha:p2 (Round to two decimal places as needed.) О в. Но: р2 ,Haip< (Round to two decimal places as needed.) O C. Ho: p# ,Ha:p= (Round to two decimal places as needed.) O D. Ho: ps Ha p> (Round to two decimal places as needed.) O E. Ho: p> .Haips (Round to two decimal places as needed.) OF. Ho: p= , Ha:p# (Round to two decimal places as needed.) O G. A normal sampling distribution cannot be used. If a normal sampling distribution can be used, identify the critical value(s) for this test. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. O A. Zn =

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### Normal Sampling Distribution and Hypothesis Testing

**Problem Description:**
You need to determine whether a normal sampling distribution can be used, given the following parameters:
- \( p \): the population proportion 
- \( \alpha \): the level of significance 
- \( \hat{p} \): the sample proportion 
- \( n \): the sample size 

**Given Data:**
- Claim: \( p > 0.67 \)
- \( \alpha = 0.06 \)
- Sample statistics: \( \hat{p} = 0.72 \)
- \( n = 325 \)

#### Step 1: Check the Normal Sampling Distribution Condition
A normal sampling distribution can be used if:
1. \( nq \geq 5 \) 
2. \( n(1-\hat{p}) \geq 5 \) 

Where:
- \( q = 1 - p \)
- \( \hat{q} = 1 - \hat{p} \)

*Insert the appropriate values in the interactive fields provided to check these conditions.*

#### Step 2: Formulate Hypotheses
If the normal sampling distribution conditions are met, then identify the hypotheses for testing the claim. Round to two decimal places as needed.

1. **Options to choose from:**
   - **(A)** \( H_0: p < \square, \quad H_a: p \geq \square \)
   - **(B)** \( H_0: p \geq \square, \quad H_a: p < \square \)
   - **(C)** \( H_0: p \ne \square, \quad H_a: p = \square \)
   - **(D)** \( H_0: p \leq \square, \quad H_a: p > \square \)
   - **(E)** \( H_0: p > \square, \quad H_a: p \leq \square \)
   - **(F)** \( H_0: p = \square, \quad H_a: p \ne \square \)
   - **(G)** A normal sampling distribution cannot be used.

2. Based on the claim \( p > 0.67 \), select the appropriate hypothesis framework.

#### Step 3: Identify Critical Value(s) 
If a normal sampling distribution can be used, identify the critical
Transcribed Image Text:### Normal Sampling Distribution and Hypothesis Testing **Problem Description:** You need to determine whether a normal sampling distribution can be used, given the following parameters: - \( p \): the population proportion - \( \alpha \): the level of significance - \( \hat{p} \): the sample proportion - \( n \): the sample size **Given Data:** - Claim: \( p > 0.67 \) - \( \alpha = 0.06 \) - Sample statistics: \( \hat{p} = 0.72 \) - \( n = 325 \) #### Step 1: Check the Normal Sampling Distribution Condition A normal sampling distribution can be used if: 1. \( nq \geq 5 \) 2. \( n(1-\hat{p}) \geq 5 \) Where: - \( q = 1 - p \) - \( \hat{q} = 1 - \hat{p} \) *Insert the appropriate values in the interactive fields provided to check these conditions.* #### Step 2: Formulate Hypotheses If the normal sampling distribution conditions are met, then identify the hypotheses for testing the claim. Round to two decimal places as needed. 1. **Options to choose from:** - **(A)** \( H_0: p < \square, \quad H_a: p \geq \square \) - **(B)** \( H_0: p \geq \square, \quad H_a: p < \square \) - **(C)** \( H_0: p \ne \square, \quad H_a: p = \square \) - **(D)** \( H_0: p \leq \square, \quad H_a: p > \square \) - **(E)** \( H_0: p > \square, \quad H_a: p \leq \square \) - **(F)** \( H_0: p = \square, \quad H_a: p \ne \square \) - **(G)** A normal sampling distribution cannot be used. 2. Based on the claim \( p > 0.67 \), select the appropriate hypothesis framework. #### Step 3: Identify Critical Value(s) If a normal sampling distribution can be used, identify the critical
**Determining the Use of a Normal Sampling Distribution for Hypothesis Testing**

For the following information, determine whether a normal sampling distribution can be used, where \( p \) is the population proportion, \( \alpha \) is the level of significance, \( \hat{p} \) is the sample proportion, and \( n \) is the sample size. If it can be used, test the claim.

**Claim:** \( p > 0.67 \); \( \alpha = 0.06 \). **Sample Statistics:** \( \hat{p} = 0.72, n = 325 \)

**Step 1**: Determine if a normal sampling distribution can be used. If it can, identify the critical value(s) for this test. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.

- **A.** \( z_0 = \) [ ]
  - *(Round to two decimal places as needed. Use a comma to separate answers as needed.)*
- **B.** A normal sampling distribution cannot be used.

**Step 2**: If a normal sampling distribution can be used, identify the rejection region(s). Select the correct choice below and, if necessary, fill in the answer box(es) to complete your choice.

- **A.** The rejection region is \( [ \_\_\_ < z < \_\_\_ ] \)
  - *(Round to two decimal places as needed.)*
- **B.** The rejection region is \( z < \_\_\_ \)
  - *(Round to two decimal places as needed.)*
- **C.** The rejection regions are \( z < \_\_\_ \) and \( z > \_\_\_ \)
  - *(Round to two decimal places as needed.)*
- **D.** The rejection region is \( z > \_\_\_ \)
  - *(Round to two decimal places as needed.)*
- **E.** A normal sampling distribution cannot be used.

This step-by-step process helps in deciding the appropriate statistical approach for testing the given claim using the provided sample statistics.
Transcribed Image Text:**Determining the Use of a Normal Sampling Distribution for Hypothesis Testing** For the following information, determine whether a normal sampling distribution can be used, where \( p \) is the population proportion, \( \alpha \) is the level of significance, \( \hat{p} \) is the sample proportion, and \( n \) is the sample size. If it can be used, test the claim. **Claim:** \( p > 0.67 \); \( \alpha = 0.06 \). **Sample Statistics:** \( \hat{p} = 0.72, n = 325 \) **Step 1**: Determine if a normal sampling distribution can be used. If it can, identify the critical value(s) for this test. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. - **A.** \( z_0 = \) [ ] - *(Round to two decimal places as needed. Use a comma to separate answers as needed.)* - **B.** A normal sampling distribution cannot be used. **Step 2**: If a normal sampling distribution can be used, identify the rejection region(s). Select the correct choice below and, if necessary, fill in the answer box(es) to complete your choice. - **A.** The rejection region is \( [ \_\_\_ < z < \_\_\_ ] \) - *(Round to two decimal places as needed.)* - **B.** The rejection region is \( z < \_\_\_ \) - *(Round to two decimal places as needed.)* - **C.** The rejection regions are \( z < \_\_\_ \) and \( z > \_\_\_ \) - *(Round to two decimal places as needed.)* - **D.** The rejection region is \( z > \_\_\_ \) - *(Round to two decimal places as needed.)* - **E.** A normal sampling distribution cannot be used. This step-by-step process helps in deciding the appropriate statistical approach for testing the given claim using the provided sample statistics.
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