To calculate the margin of error, we can use the formula:
\[ \text{Margin of Error} = z \times \sqrt{\frac{p(1-p)}{n}} \]
Where:
- \( z \) is the z-score (1.96 for 95% confidence),
- \( p \) is the sample proportion,
- \( n \) is the sample size.
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Calculate the sample proportion \( p \):
- \( p = \frac{x}{n} = \frac{19}{250} = 0.076 \)
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Calculate \( 1 - p \):
- \( 1 - p = 1 - 0.076 = 0.924 \)
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Calculate the sample size \( n \):
- \( n = 250 \)
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Calculate the margin of error: \[ \text{Margin of Error} = 1.96 \times \sqrt{\frac{0.076 \times 0.924}{250}} \]
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Calculating the inside of the square root:
- \( 0.076 \times 0.924 = 0.070224 \)
- \( \frac{0.070224}{250} = 0.000280896 \)
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Taking the square root:
- \( \sqrt{0.000280896} \approx 0.0168 \)
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Final calculation: \[ \text{Margin of Error} = 1.96 \times 0.0168 \approx 0.0330 \]
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Convert the margin of error into a percentage:
- \( 0.0330 \times 100 = 3.3% \)
Therefore, the margin of error is 3.3%.
The correct response is:
3.3%