1. What is the Sample Size Calculator?

The Sample Size Calculator helps determine the number of respondents needed for a survey to achieve statistically significant results, based on your desired confidence level, expected proportion, and margin of error.

2. How Does the Calculator Work?

The calculator uses the sample size formula:

Where:

• \( n \) — Required sample size
• \( z \) — Z-score (standard score for confidence level)
• \( p \) — Expected proportion (0-1)
• \( e \) — Margin of error (0-1)

Explanation: The formula calculates how many respondents you need to achieve results within your desired margin of error at your chosen confidence level.

3. Importance of Sample Size Calculation

Details: Proper sample size ensures your survey results are statistically valid and representative of your target population. Too small a sample may yield unreliable results, while too large wastes resources.

4. Using the Calculator

Tips:

• For most surveys, use 95% confidence (z = 1.96)
• When unsure of proportion, use p = 0.5 (most conservative estimate)
• Common margin of error values are 0.05 (5%) or 0.03 (3%)

5. Frequently Asked Questions (FAQ)

Q1: What confidence level should I use?
A: 95% is standard for most research. Use 99% for highly critical studies or 90% for exploratory research.

Q2: What if I don't know the expected proportion?
A: Use 0.5 (50%) as this gives the largest possible sample size, ensuring your results will be valid regardless of actual proportion.

Q3: How does margin of error affect sample size?
A: Smaller margins require larger samples. Halving the margin of error quadruples the required sample size.

Q4: Does this work for small populations?
A: For populations under 20,000, use the finite population correction factor: \( n_{adj} = \frac{n}{1 + \frac{(n - 1)}{N}} \) where N is population size.

Q5: What about response rates?
A: Adjust your sample size upward to account for expected non-response (e.g., if you need 400 and expect 50% response rate, survey 800).