Question
Why do you round the sample size up?
Because you cannot collect a fraction of an observation, and rounding up keeps the margin-of-error target intact.
Math
Use OmniCalc's sample size calculator to estimate how many observations you need for a target margin of error at a chosen confidence level.
Sample size calculator
Enter a standard deviation, target margin of error, and confidence level to estimate a z-based sample size for a mean.
Why this result matters
A natural next-step stats page that helps users plan studies and surveys by sizing samples from variance, precision, and confidence goals. Use the tool above to enter a few clear inputs and get a practical answer you can use right away.
This sample size calculator helps students, researchers, and analysts estimate how many observations they need before collecting data. Enter an expected standard deviation, a target margin of error, and a confidence level to get a quick z-based sample size estimate for a mean.
Formula and method
The calculator uses the z-based sample-size formula for a mean: n = (critical value × standard deviation / margin of error)^2, then rounds up to the next whole number.
Example
If the standard deviation is 12, the target margin of error is 4, and the confidence level is 95%, the formula gives about 34.57, so you should plan for 35 observations.
FAQ
Short answers to the questions people often ask before or after using the tool.
Question
Because you cannot collect a fraction of an observation, and rounding up keeps the margin-of-error target intact.
Question
A tighter precision goal leaves less room for sampling noise, so the sample size has to increase to compensate.
Question
Higher confidence uses a larger critical value, which pushes the required sample size up.
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