Systematic Sample vs Cluster Sample
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Systematic sample
Collecting data and study design
A systematic sample orders the population, picks a random starting point, then selects every kth individual from that point onward.
Systematic sampling chooses one random start and then follows a fixed interval, which is handy when a full list is hard to number in advance. For example, standing at a store entrance and surveying every 10th customer after a random start is a systematic sample. The gap between selections, often written (the sampling interval), is set so the selections cover the whole population. It can fail if the list has a repeating pattern that lines up with the interval.
Cluster sample
Collecting data and study design
A cluster sample divides the population into groups called clusters, randomly selects whole clusters, and includes every individual in the chosen clusters.
Cluster sampling is used when the population naturally falls into groups that are each meant to resemble the whole population. For example, to survey a school district you might randomly choose 5 schools and then survey every student in those 5 schools. Unlike strata, clusters are ideally diverse within and similar to one another, and you sample entire clusters rather than individuals. It is often cheaper because you only travel to a few locations.