Which sampling method involves selecting groups or clusters rather than individuals?

Cluster sampling is a method in which researchers divide the population into distinct groups or clusters, and then randomly select entire clusters for study rather than selecting individuals from the population. This approach is particularly useful when the population is large and spread out geographically, as it can be more practical and cost-effective to analyze complete groups rather than individual members.

In cluster sampling, the clusters are usually pre-existing groups or natural divisions within the population, such as schools, neighborhoods, or communities. Once clusters are selected, every member within those chosen clusters may be surveyed or sampled, or a random sample may be taken from within the selected clusters. This method helps in reducing costs and improving efficiency, making it a popular choice for researchers conducting large-scale studies.