Online Sampling Tool
A statistical planning tool that helps researchers determine required sample size or margin of error for surveys, using population size, confidence level, and estimated proportion.
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About This Tool
Conceptually it uses standard proportion-based formulas. For a given margin of error E and confidence level, n0 = (Z^2 * p(1-p)) / E^2, and if a finite population size N is supplied, n = n0 / (1 + (n0 - 1)/N). The tool also supports computing E for a given n, N, and p. Defaults use p = 0.5 for a conservative estimate.
Outputs include the recommended sample size, the corresponding margin of error, the Z-score for the chosen level, and whether finite population correction was applied. The approach is explicit about assumptions and returns rounded values to avoid under- or over-sampling. It is suitable for quick feasibility checks, budget planning, and educational uses.
Why it differs: it presents domain-specific calculations with clear inputs and outputs, avoiding design effects, weighting, or multi-stage designs by default; users can adjust inputs to reflect these complexities manually if needed.
How to Use
- Provide inputs: population_size (optional), confidence_level (90/95/
- , and either margin_of_error (percent) or set mode to calculate sample size. Set estimated_proportion_p (default
- .
- Choose mode: 'sample_size' to compute n for your MOE, or 'margin_of_error' to find E for a given n.
- Run calculation to obtain outputs: recommended sample size, MOE, Z-score, and FPC flag.
- Review outputs and adjust for real-world constraints (response rate, design effects) by inflating n if needed.
- Export or save the results for documentation.
Frequently Asked Questions
Find Quick Answers
What is this tool best used for?
How does finite population correction affect results?
What if I don't know p?
What sampling assumptions are made?
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