5. Is the response rate for questionnaires affected by including some sort of incentive to respond along with the questionnaire? In one experiment, 110 questionnaires with no incentive re- sulted in 75 being returned, whereas 98 questionnaires that included a chance to win a lottery yielded 66 responses. Test the claim at a = 0.05 that including an incentive will increase the likelihood of a response using classical approach. Please show all 4 steps clearly and interpret your conclusion.
5. Is the response rate for questionnaires affected by including some sort of incentive to respond along with the questionnaire? In one experiment, 110 questionnaires with no incentive re- sulted in 75 being returned, whereas 98 questionnaires that included a chance to win a lottery yielded 66 responses. Test the claim at a = 0.05 that including an incentive will increase the likelihood of a response using classical approach. Please show all 4 steps clearly and interpret your conclusion.
MATLAB: An Introduction with Applications
6th Edition
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Author:Amos Gilat
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![### Question 5
**Research Question:** Is the response rate for questionnaires affected by including some sort of incentive to respond along with the questionnaire?
#### Experimental Details:
- **Without Incentive:**
- Total questionnaires: 110
- Returned: 75
- **With Incentive (chance to win a lottery):**
- Total questionnaires: 98
- Returned: 66
#### Task:
Test the claim at a significance level of \(\alpha = 0.05\) that including an incentive will increase the likelihood of a response using the classical approach.
**Instructions:**
Please show all 4 steps clearly and interpret your conclusion.
### Solution Steps (Classical Approach):
1. **State the Hypotheses:**
- Null Hypothesis (\(H_0\)): There is no difference in the response rates with or without incentive.
- Alternative Hypothesis (\(H_A\)): The response rate with an incentive is higher than the response rate without incentive.
2. **Choose the Significance Level:**
- \(\alpha = 0.05\)
3. **Select the Appropriate Test Statistic:**
- Since we are testing for proportions, we use the Z-test for the difference between two proportions.
4. **Calculate the Test Statistic and P-Value:**
\[ \hat{p}_1 = \frac{75}{110} \approx 0.682 \]
\[ \hat{p}_2 = \frac{66}{98} \approx 0.673 \]
\[ \hat{p} = \frac{75 + 66}{110 + 98} \approx 0.678 \]
\[ z = \frac{\hat{p}_1 - \hat{p}_2}{\sqrt{\hat{p}(1 - \hat{p})\left( \frac{1}{110} + \frac{1}{98} \right)}} \]
Insert the respective values to find the Z-score.
5. **Decision Rule:**
- Compare the Z-score with the critical value from the Z-table at \(\alpha = 0.05\) for a one-tailed test.
6. **Conclusion:**
- If the calculated Z value exceeds the critical value, reject \(H_0\) and conclude that offering an incentive indeed increases the response rate.
**Note:** Steps 4 and 5 would require mathematical computation](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F322ab9b5-8b73-42ca-a79a-5c7ee3611144%2Faafe8b0b-3ac4-45b5-9e9a-3368d8349b54%2F47kspzl9_processed.jpeg&w=3840&q=75)
Transcribed Image Text:### Question 5
**Research Question:** Is the response rate for questionnaires affected by including some sort of incentive to respond along with the questionnaire?
#### Experimental Details:
- **Without Incentive:**
- Total questionnaires: 110
- Returned: 75
- **With Incentive (chance to win a lottery):**
- Total questionnaires: 98
- Returned: 66
#### Task:
Test the claim at a significance level of \(\alpha = 0.05\) that including an incentive will increase the likelihood of a response using the classical approach.
**Instructions:**
Please show all 4 steps clearly and interpret your conclusion.
### Solution Steps (Classical Approach):
1. **State the Hypotheses:**
- Null Hypothesis (\(H_0\)): There is no difference in the response rates with or without incentive.
- Alternative Hypothesis (\(H_A\)): The response rate with an incentive is higher than the response rate without incentive.
2. **Choose the Significance Level:**
- \(\alpha = 0.05\)
3. **Select the Appropriate Test Statistic:**
- Since we are testing for proportions, we use the Z-test for the difference between two proportions.
4. **Calculate the Test Statistic and P-Value:**
\[ \hat{p}_1 = \frac{75}{110} \approx 0.682 \]
\[ \hat{p}_2 = \frac{66}{98} \approx 0.673 \]
\[ \hat{p} = \frac{75 + 66}{110 + 98} \approx 0.678 \]
\[ z = \frac{\hat{p}_1 - \hat{p}_2}{\sqrt{\hat{p}(1 - \hat{p})\left( \frac{1}{110} + \frac{1}{98} \right)}} \]
Insert the respective values to find the Z-score.
5. **Decision Rule:**
- Compare the Z-score with the critical value from the Z-table at \(\alpha = 0.05\) for a one-tailed test.
6. **Conclusion:**
- If the calculated Z value exceeds the critical value, reject \(H_0\) and conclude that offering an incentive indeed increases the response rate.
**Note:** Steps 4 and 5 would require mathematical computation
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