What sampling method involves selecting one individual at random and then choosing additional people at evenly spaced intervals?

The method described in the question is a systematic sample. This sampling technique involves selecting a starting point randomly and then choosing additional individuals at fixed, regular intervals from that point onward. For example, if a researcher selected the first participant randomly and subsequently chose every 10th person on a list, this would illustrate systematic sampling.

Systematic sampling is particularly useful when a complete list of the population is accessible and allows researchers to efficiently gather data while still maintaining a degree of randomness in the selection process. By using this method, researchers can ensure a diverse sample while making the process of selecting subjects more straightforward compared to other sampling techniques. This approach can help to eliminate bias that might occur if the selection were purely based on convenience or judgement.

In the context of the other sampling methods, cluster sampling involves dividing the population into groups (or clusters) and then randomly selecting entire groups. A simple random sample ensures every member of the population has an equal chance of being selected, often through randomized methods without intervals. Stratified sampling involves dividing the population into distinct subgroups and then randomly sampling from those specific strata, which serves a different purpose, focusing more on ensuring representation from various segments.