Sample Size Calculator
Calculate required sample size for surveys and research using confidence level, margin of error, estimated proportion, and optional population size.
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Required Sample 370
Large Population Sample 385
Recommended Invitations 925
How It Works
This calculator estimates the minimum sample size for a proportion. It starts with the standard large-population formula, then optionally applies finite population correction when you provide a population size.
Formula
n = z^2 x p x (1-p) / e^2
Adjusted n = n / (1 + ((n - 1) / N))
Frequently Asked Questions
- For a proportion, a common formula is n = z^2 x p x (1-p) / e^2, where z is the z-score for the confidence level, p is the expected proportion, and e is the margin of error.
- It depends on your margin of error and expected proportion. If you use 95% confidence, 5% margin of error, and an unknown proportion of 50%, the common result is about 385 responses for a large population.
- Using 50% is conservative because it produces the largest required sample size. If you do not know the expected proportion, 50% is often the safest assumption.
- Margin of error is the amount of uncertainty you are willing to accept in the estimate. A smaller margin of error means you need a larger sample size.
- If your population is limited and known, you can adjust the large-population sample size downward with a finite population correction. This prevents oversampling when the total population is small.
- 95% is the most common choice for surveys and research. 90% uses a smaller sample, while 99% requires a larger sample because it aims for more certainty.
- Yes. If only part of the people you contact will respond, you should invite more people than the minimum sample size. Divide the required sample by the expected response rate to estimate invites needed.
- Yes. This calculator is useful for surveys, polling, market research, audits, and many academic projects where you want to estimate a proportion with a target confidence level and margin of error.