1. What is the Sample Size Formula?

The sample size formula calculates the number of participants needed in a study to achieve statistically significant results. It ensures that research findings are reliable and representative of the population being studied.

2. How Does the Calculator Work?

The calculator uses the sample size formula:

Where:

• \( n \) — Required sample size
• \( Z \) — Z-score (standard score)
• \( p \) — Estimated proportion or probability
• \( E \) — Margin of error

Explanation: The formula determines the minimum number of observations needed to achieve a desired level of precision in statistical estimates.

3. Importance of Sample Size Calculation

Details: Proper sample size calculation is crucial for research validity. It helps avoid underpowered studies (too few participants) or wasteful oversampling (too many participants).

4. Using the Calculator

Tips: Enter the Z-score corresponding to your confidence level (e.g., 1.96 for 95% confidence), the estimated proportion (use 0.5 for maximum variability), and your desired margin of error.

5. Frequently Asked Questions (FAQ)

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

Q2: What if I don't know the proportion?
A: Use 0.5 (50%) as this provides the most conservative (largest) sample size estimate.

Q3: What is a reasonable margin of error?
A: Typically 3-5% for most surveys, but this depends on your research requirements and available resources.

Q4: Does this work for all study types?
A: This formula is primarily for estimating proportions in surveys. Different formulas exist for means, correlations, and other statistical measures.

Q5: What about population size?
A: This formula assumes an infinite population. For finite populations, a finite population correction factor should be applied.