Sampling Interval Calculator
Find the systematic sampling interval for a population and a target sample size.
How the sampling interval works
Systematic sampling selects every k-th unit from an ordered list, after a random starting point. The interval k is the population size divided by the target sample size.
It is a practical alternative to simple random sampling when you have a complete list (a sampling frame) and want a fast, evenly spread sample. The interval is rounded down to a whole number so you never skip past the end of the frame.
The method assumes the list has no periodic pattern that could bias the selection. A random start keeps the sample approximately random.
The formula
k = floor(N ÷ n)
Divide the population size N by the required sample size n and round down. Choose a random starting point between 1 and k, then select every k-th unit.
Worked example
A population of 5,000 and a sample of 250
k = 5,000 ÷ 250 = 20. Pick a random start between 1 and 20, then select every 20th unit from the list.
Frequently asked questions
Why round the interval down?
Rounding down keeps the selected units within the population frame and ensures you can still reach your target sample size from a random start.
Is systematic sampling random?
It is approximately random when the list has no hidden order. A random starting point prevents bias, but periodic patterns in the list can still cause problems.
What if the sample size equals the population?
Then k = 1 and every unit is selected — you are conducting a census of the population rather than a sample.
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