What is systematic sampling?

Systematic sampling is a method where individuals are selected from a larger population by choosing every nth individual from a list, after starting from a randomly selected point. This ensures that the selection process is spread out and unbiased, as it does not rely on convenience or judgement. By beginning with a random start, systematic sampling maintains the randomness necessary to give every individual an equal chance of being included in the sample, while also providing a structured approach to sampling.

This method is particularly useful in research when the population is organized in a way that allows for easy access to a complete list of individuals, which can then be navigated systematically to select the sample. Unlike convenience sampling, which can lead to bias due to the ease of access to certain groups, or snowball sampling that relies on existing subjects to recruit further subjects, systematic sampling provides a more objective framework. It also does not inherently favor large sample sizes, making it distinct from methods that might prioritize larger cohorts.