How to Calculate Required Sample Size
Sample size determines how representative a survey or study is of the population it aims to describe. Too small a sample produces unreliable, misleading results. Too large wastes resources. The sample size formula balances confidence level, margin of error, and population size to find the minimum number of responses needed for statistically valid conclusions.
Google ad
Formula
Sample Size Calculator
Calculate the required sample size for a statistically valid survey or study.
Google ad
Worked Example
Given:
Related Calculators
FAQs
Why does population size barely affect sample size for large populations?
For populations over 10,000, the required sample size barely changes because the finite population correction factor approaches 1. This is why national polls of 1,000–2,000 people can reliably represent hundreds of millions — what matters most is sample size, not the fraction of the population sampled.
What does margin of error mean?
Margin of error is the maximum expected difference between your sample result and the true population value. A 5% margin of error means your result could be up to 5 percentage points above or below the true value. Halving the margin of error quadruples the required sample size.
What proportion should I assume if I don't know?
Use p = 0.5 (50%) when you have no prior information. This is the most conservative assumption — it maximises the required sample size, ensuring you have enough data regardless of the true proportion. Using p = 0.5 is standard practice for planning surveys.