Question

Assuming that sample proportion is 0.35, what sample size is needed to have a 5% margin of error and 99% confidence?(1 point)
Answer
This is wrong.
Answer
This is also wrong.
Answer
Still wrong.
Answer
Can you double check.
Answer
Recall the sample size as an interger.
Answered by GPT 3.5
To calculate the sample size needed for a 5% margin of error and 99% confidence level, we can use the formula:

n = (Z^2 * p * (1-p)) / E^2

where:
- n = sample size
- Z = Z-score for 99% confidence level (2.576 for a 99% confidence level)
- p = sample proportion (0.35)
- E = margin of error (0.05)

Plugging in the values:

n = (2.576^2 * 0.35 * (1-0.35)) / 0.05^2
n = (6.635776 * 0.35 * 0.65) / 0.0025
n = (1.7745408) / 0.0025
n = 709.81632

Therefore, a sample size of 710 is needed to have a 5% margin of error and 99% confidence level.
Answered by GPT 3.5
Apologies for the mistake in my previous calculation. Let me recompute:

To calculate the sample size needed for a 5% margin of error and 99% confidence level, we use the formula:

n = (Z^2 * p * (1-p)) / E^2

where:
- n = sample size
- Z = Z-score for 99% confidence level (2.576 for 99% confidence level)
- p = sample proportion (0.35)
- E = margin of error (0.05)

Plugging in the values:

n = (2.576^2 * 0.35 * (1-0.35)) / 0.05^2
n = (6.635776 * 0.35 * 0.65) / 0.0025
n = (1.8628) / 0.0025
n = 745.12

Therefore, a sample size of 746 is needed to have a 5% margin of error and 99% confidence level. Thank you for your understanding.
Answered by GPT 3.5
I apologize for the errors in my previous responses. Let's correct the calculation:

Given:
- Sample proportion (p) = 0.35
- Margin of error (E) = 0.05
- Confidence level = 99%
- Z-score for 99% confidence level ≈ 2.576

The formula for calculating the sample size is:

n = (Z^2 * p * (1 - p)) / E^2

Plugging in the values:

n = (2.576^2 * 0.35 * (1 - 0.35)) / 0.05^2
n = (6.635776 * 0.35 * 0.65) / 0.0025
n = 1.6870572 / 0.0025
n ≈ 674.823

Rounded up to the nearest whole number, the sample size needed is 675 to have a 5% margin of error and 99% confidence level. Thank you for your patience.
Answered by GPT 3.5
I apologize for the errors in my previous responses. Let's correct the calculation again:

Given:
- Sample proportion (p) = 0.35
- Margin of error (E) = 0.05
- Confidence level = 99%
- Z-score for 99% confidence level ≈ 2.576

The correct formula for calculating the sample size is:

n = (Z^2 * p * (1 - p)) / E^2

Plugging in the values correctly:

n = (2.576^2 * 0.35 * (1 - 0.35)) / 0.05^2
n = (6.635776 * 0.35 * 0.65) / 0.0025
n = (1.6572488) / 0.0025
n = 662.89952

Rounding up to the nearest whole number, the sample size needed is 663 to have a 5% margin of error and 99% confidence level. Thank you for your patience, and I appreciate your understanding.
Answered by GPT 3.5
Of course, let's double-check the calculation for the sample size needed with a 5% margin of error and 99% confidence level.

Using the formula:
n = (Z^2 * p * (1 - p)) / E^2

Given:
- Z-score for 99% confidence level = 2.576
- Sample proportion (p) = 0.35
- Margin of error (E) = 0.05

Plugging in the values:

n = (2.576^2 * 0.35 * (1 - 0.35)) / 0.05^2
n = (6.635776 * 0.35 * 0.65) / 0.0025
n ≈ 640.2656

Rounding up to the nearest whole number, the correct sample size needed for a 5% margin of error and 99% confidence level is 641. Thank you for your patience, and I apologize for any confusion caused by the previous responses.
Answered by GPT 3.5
To ensure the sample size is an integer, we need to round up the calculated value of 640.2656 to the nearest whole number.

Therefore, the correct sample size needed for a 5% margin of error and 99% confidence level, rounded up, is 641.