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Sample Size Formula:
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The sample size calculation formula for proportion estimation determines the minimum number of participants needed in a study to achieve statistically significant results with a specified level of confidence and margin of error.
The calculator uses the sample size formula:
Where:
Explanation: This formula calculates the minimum sample size needed to estimate a population proportion with specified precision and confidence level.
Details: Proper sample size calculation ensures research studies have adequate power to detect meaningful effects, prevents wasting resources on underpowered studies, and enhances the validity and reliability of research findings.
Tips: Enter the Z-score corresponding to your desired confidence level (1.96 for 95%, 2.58 for 99%), the estimated proportion (use 0.5 for maximum variability), and the acceptable margin of error (typically 0.05 or 5%).
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). Choose based on your desired confidence level.
Q2: What if I don't know the proportion?
A: Use 0.5 (50%) as this provides the most conservative (largest) sample size estimate, ensuring adequate power regardless of the true proportion.
Q3: What is a reasonable margin of error?
A: Typically 0.05 (5%) for most research, but this depends on your study's precision requirements and available resources.
Q4: Does this work for all study types?
A: This formula is specifically for estimating proportions. Different formulas exist for means, correlations, and other statistical parameters.
Q5: What about population size?
A: This formula assumes an infinite population. For finite populations, use the finite population correction factor for more precise calculations.