1. What is a Sample Size Calculator?

Definition: This calculator determines the minimum number of participants needed in a research survey to achieve statistically significant results.

Purpose: It helps researchers design studies with adequate power while optimizing resource allocation.

2. How Does the Calculator Work?

The calculator uses the formula:

Where:

• \( n \) — Required sample size
• \( Z \) — Z-score corresponding to desired confidence level (1.96 for 95%)
• \( p \) — Estimated proportion (0.5 for maximum variability)
• \( e \) — Margin of error (decimal, e.g., 0.05 for ±5%)

Explanation: The formula balances confidence level, expected variability, and desired precision to determine the minimum sample needed.

3. Importance of Sample Size Calculation

Details: Proper sample size ensures study validity, prevents underpowered results, and helps allocate research resources efficiently.

4. Using the Calculator

Tips: Enter the Z-score (1.96 for 95% CI), estimated proportion (0.5 if uncertain), and margin of error (typically 0.05-0.10).

5. Frequently Asked Questions (FAQ)

Q1: What Z-score should I use?
A: Common values are 1.645 (90% CI), 1.96 (95% CI), and 2.576 (99% CI).

Q2: Why use 0.5 for proportion?
A: 0.5 gives the most conservative (largest) sample size as it maximizes p*(1-p).

Q3: What's a reasonable margin of error?
A: Typically 5% (0.05) for academic research, though 10% may be acceptable for exploratory studies.

Q4: Does this work for small populations?
A: For populations under 10,000, consider using a finite population correction factor.

Q5: What if I have multiple groups?
A: Calculate sample size for each group separately and sum them.