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The image contains a mathematical equation related to sample size calculation for a proportion. Here's a transcription of the formula:

\[
n = \frac{804 \times 1.96^2 \times 0.3 \times (0.5)}{804 - 1 + (0.065^2 \times 1.96^2 \times (0.5) \times (0.5))} = 261
\]

This seems to be a sample size calculation for a survey or experiment, possibly using an estimated proportion and confidence interval formula.

Would you like a detailed explanation of how this sample size calculation works? Let me know if you have specific questions or would like further clarification.

Here are five questions related to this formula:

1. What is the significance of the value 1.96 in sample size calculations?
2. How do you interpret the values 0.3 and 0.5 in this context?
3. What role does the value 804 play in this equation?
4. How does adjusting the confidence level impact the final sample size?
5. How would changing the error margin (e.g., the value 0.065) affect the calculation?

**Tip:** The value 1.96 corresponds to a 95% confidence level in a normal distribution.

The image contains a mathematical equation related to sample size calculation for a proportion.

Understand the sample size calculation for a proportion using a confidence level of 95%. This example walks through the formula where 1.96 is the Z-value, 804 is the population size, 0.065 is the error margin, and 0.3 is the estimated proportion. The resulting sample size is 261.

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