c) If you take a sample of size 571 from the original population where p is 5%, can we say that the sampling distribution of p is approximately normal? Why or why not? Check conditions: 1. np- which 2. n(1 - p) - which 3. and N- which Can we say that the sampling distribution of p is approximately normal in this case? (If the answer is no, state the first conditions in the list above that failed) Yes, since all 3 conditions check out d) Redo part c assuming the population only has 6574 people in it. Check conditions: 1. np- which 2. n(1 - p) - which 3. and N- which Can we say that the sampling distribution of p is approximately normal in this case?

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please complete parts C and D!!

### Sampling Distribution and Normality

#### Exercise c

**Scenario:**  
You are taking a sample of size 571 from an original population where the true proportion \( p \) is 5%. Can the sampling distribution of \( \hat{p} \) be considered approximately normal? Let's evaluate based on the conditions for normality:

- **Condition 1:** \( np = \_\_\_ \)  
  - Criteria: \( \geq 10 \)
  - Result: ✔️ (meets the condition)

- **Condition 2:** \( n(1 - p) = \_\_\_ \)  
  - Criteria: \( \geq 10 \)
  - Result: ✔️ (meets the condition)

- **Condition 3:** \( n \leq 0.05N \)  
  - Criteria: \( \_\_\_ \)
  - Result: ✔️ (meets the condition)

**Conclusion:**  
Yes, since all 3 conditions are satisfied, the sampling distribution of \( \hat{p} \) is approximately normal.

#### Exercise d

**Scenario with Modified Population Size:**  
Redo the evaluation in part c, assuming the population only has 6574 people.

- **Condition 1:** \( np = \_\_\_ \)  
  - Criteria: \( \geq 10 \)
  - Result: ✔️ (meets the condition)

- **Condition 2:** \( n(1 - p) = \_\_\_ \)  
  - Criteria: \( \geq 10 \)
  - Result: ✔️ (meets the condition)

- **Condition 3:** \( n \leq 0.05N \)  
  - Criteria: \( \_\_\_ \)
  - Result: ❌ (does not meet the condition)

**Conclusion:**  
No, because the third condition did not satisfy the criteria, the sampling distribution of \( \hat{p} \) cannot be considered approximately normal in this case.
Transcribed Image Text:### Sampling Distribution and Normality #### Exercise c **Scenario:** You are taking a sample of size 571 from an original population where the true proportion \( p \) is 5%. Can the sampling distribution of \( \hat{p} \) be considered approximately normal? Let's evaluate based on the conditions for normality: - **Condition 1:** \( np = \_\_\_ \) - Criteria: \( \geq 10 \) - Result: ✔️ (meets the condition) - **Condition 2:** \( n(1 - p) = \_\_\_ \) - Criteria: \( \geq 10 \) - Result: ✔️ (meets the condition) - **Condition 3:** \( n \leq 0.05N \) - Criteria: \( \_\_\_ \) - Result: ✔️ (meets the condition) **Conclusion:** Yes, since all 3 conditions are satisfied, the sampling distribution of \( \hat{p} \) is approximately normal. #### Exercise d **Scenario with Modified Population Size:** Redo the evaluation in part c, assuming the population only has 6574 people. - **Condition 1:** \( np = \_\_\_ \) - Criteria: \( \geq 10 \) - Result: ✔️ (meets the condition) - **Condition 2:** \( n(1 - p) = \_\_\_ \) - Criteria: \( \geq 10 \) - Result: ✔️ (meets the condition) - **Condition 3:** \( n \leq 0.05N \) - Criteria: \( \_\_\_ \) - Result: ❌ (does not meet the condition) **Conclusion:** No, because the third condition did not satisfy the criteria, the sampling distribution of \( \hat{p} \) cannot be considered approximately normal in this case.
Assume you have a population of 22,000 people where 5% of the population has some particular disease.
Transcribed Image Text:Assume you have a population of 22,000 people where 5% of the population has some particular disease.
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