# How Systematic Sampling Works

## What It Is and How to Do It

Systematic sampling is a technique for creating a random probability sample in which each piece of data is chosen at a fixed interval for inclusion in the sample. For example, if a researcher wanted to create a systematic sample of 1,000 students at a university with an enrolled population of 10,000, he or she would choose every tenth person from a list of all students.

## How to Create a Systematic Sample

Creating a systematic sample is rather easy. The researcher must first decide how many people out of the total population to include in the sample, keeping in mind that the larger the sample size, the more accurate, valid, and applicable the results will be. Then, the researcher will decide what the interval for sampling is, which will be the standard distance between each sampled element. This should be decided by dividing the total population by the desired sample size. In the example given above, the sampling interval is 10 because it is the result of dividing 10,000 (the total population) by 1,000 (the desired sample size). Finally, the researcher chooses an element from the list that falls below the interval, which in this case would be one of the first 10 elements within the sample, and then proceeds to select every tenth element.