📊 Sample Size Calculator
Running a survey and wondering how many replies make the results believable? This calculator uses Cochran's formula — the standard method pollsters rely on — to turn your margin of error and confidence level into a concrete respondent count.
If your audience is small, the finite population correction shrinks the required sample fairly: surveying 370 people out of 10,000 gives the same ±5% precision at 95% confidence as surveying 384 out of ten million.
How to use this calculator
Enter your population size, the margin of error you can live with, and your confidence level. The calculator returns the number of completed survey responses you need.
- Type the total size of the population you are studying, for example 10000 customers.
- Enter your margin of error as a percent, such as 5 for plus or minus 5 percent.
- Pick the confidence level: 90, 95 or 99 percent.
- Press Calculate and read the required sample size, rounded up to a whole respondent.
Frequently asked questions
What does this sample size calculator compute?
It computes how many survey responses you need so your results fall within your chosen margin of error at your chosen confidence level. It uses Cochran's formula with the most conservative 50 percent response split, then applies the finite population correction for your audience size.
Can you show a worked example?
With a population of 10000, a 5 percent margin of error and 95 percent confidence, the raw formula gives about 384 responses, and the finite population correction trims it to 370. That is the number of completed surveys to aim for.
Why does a smaller margin of error need so many more responses?
The margin of error sits under a square in the formula, so halving it from 5 percent to 2.5 percent roughly quadruples the required sample. Precision gets expensive fast, which is why most surveys settle on 5 percent.
What is the finite population correction?
When your audience is small, each response covers a bigger slice of it, so you need fewer replies. The correction divides the raw sample size by a factor based on your population, and it barely matters once the population passes about 100000.