Two samples are taken with the following numbers of successes and sample sizes x1 = 36 x2 = 23 n1 = 59 n2 = 53 Find a 96% confidence interval, round answers to the nearest thousandth. < pi – P2 <
Two samples are taken with the following numbers of successes and sample sizes x1 = 36 x2 = 23 n1 = 59 n2 = 53 Find a 96% confidence interval, round answers to the nearest thousandth. < pi – P2 <
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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![### Confidence Interval Calculation for Proportion Differences
#### Given Data:
Two samples are taken with the following numbers of successes and sample sizes:
- \( x_1 = 36 \)
- \( x_2 = 23 \)
- \( n_1 = 59 \)
- \( n_2 = 53 \)
#### Objective:
Find a 96% confidence interval for the difference in proportions \( p_1 - p_2 \). Round the answers to the nearest thousandth.
#### Instructions:
- Calculate the sample proportions: \( \hat{p}_1 \) and \( \hat{p}_2 \).
- Use the formula for the confidence interval of the difference between two proportions.
#### Formula:
\[
\text{Confidence Interval} = (\hat{p}_1 - \hat{p}_2) \pm Z \sqrt{\left(\frac{\hat{p}_1(1 - \hat{p}_1)}{n_1}\right) + \left(\frac{\hat{p}_2(1 - \hat{p}_2)}{n_2}\right)}
\]
Where:
- \( \hat{p}_1 = \frac{x_1}{n_1} \)
- \( \hat{p}_2 = \frac{x_2}{n_2} \)
- \( Z \) is the Z-value corresponding to the desired confidence level (for 96%, Z ≈ 2.05).
#### Steps:
1. Calculate \( \hat{p}_1 \) and \( \hat{p}_2 \):
\[
\hat{p}_1 = \frac{36}{59}, \quad \hat{p}_2 = \frac{23}{53}
\]
2. Find the standard error (SE) for the difference in proportions:
\[
SE = \sqrt{\left(\frac{\hat{p}_1(1 - \hat{p}_1)}{59}\right) + \left(\frac{\hat{p}_2(1 - \hat{p}_2)}{53}\right)}
\]
3. Multiply the SE by the Z-value for 96% confidence and apply to the difference in sample proportions to find the confidence interval:
\[
\text{Confidence Interval} = (\hat{p}_1 - \hat{p}_2) \pm](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa218d9b0-33cd-49fb-8966-615774819802%2F10851534-9d58-4a22-aa7a-2249d5a5f33a%2F3y3hm0w_processed.png&w=3840&q=75)
Transcribed Image Text:### Confidence Interval Calculation for Proportion Differences
#### Given Data:
Two samples are taken with the following numbers of successes and sample sizes:
- \( x_1 = 36 \)
- \( x_2 = 23 \)
- \( n_1 = 59 \)
- \( n_2 = 53 \)
#### Objective:
Find a 96% confidence interval for the difference in proportions \( p_1 - p_2 \). Round the answers to the nearest thousandth.
#### Instructions:
- Calculate the sample proportions: \( \hat{p}_1 \) and \( \hat{p}_2 \).
- Use the formula for the confidence interval of the difference between two proportions.
#### Formula:
\[
\text{Confidence Interval} = (\hat{p}_1 - \hat{p}_2) \pm Z \sqrt{\left(\frac{\hat{p}_1(1 - \hat{p}_1)}{n_1}\right) + \left(\frac{\hat{p}_2(1 - \hat{p}_2)}{n_2}\right)}
\]
Where:
- \( \hat{p}_1 = \frac{x_1}{n_1} \)
- \( \hat{p}_2 = \frac{x_2}{n_2} \)
- \( Z \) is the Z-value corresponding to the desired confidence level (for 96%, Z ≈ 2.05).
#### Steps:
1. Calculate \( \hat{p}_1 \) and \( \hat{p}_2 \):
\[
\hat{p}_1 = \frac{36}{59}, \quad \hat{p}_2 = \frac{23}{53}
\]
2. Find the standard error (SE) for the difference in proportions:
\[
SE = \sqrt{\left(\frac{\hat{p}_1(1 - \hat{p}_1)}{59}\right) + \left(\frac{\hat{p}_2(1 - \hat{p}_2)}{53}\right)}
\]
3. Multiply the SE by the Z-value for 96% confidence and apply to the difference in sample proportions to find the confidence interval:
\[
\text{Confidence Interval} = (\hat{p}_1 - \hat{p}_2) \pm
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