Which sampling method divides the population into clusters, randomly selects some clusters, and surveys all subjects within the chosen clusters?

Which sampling method divides the population into clusters, randomly selects some clusters, and surveys all subjects within the chosen clusters?

• A. Cluster Samples
• B. Convenience Sample
• C. Self-Selecting Sample
• D. Purposive Sampling

Answer: (A)

Cluster sampling is at work here: you first divide the population into natural groups, or clusters, then randomly select some of those clusters, and survey everyone within the chosen clusters. This approach is efficient for large or spread-out populations because you only have to collect data from entire groups rather than individuals scattered everywhere, while keeping a random element at the cluster level. It works well when clusters fairly represent the whole population, though you need enough clusters to balance potential similarity among members within the same cluster. The other methods described—convenience sampling (easy to reach), self-selecting sampling (volunteers), and purposive sampling (targeted groups)—do not involve randomly selecting clusters and surveying all members inside them, which is why cluster sampling is distinct.

Cluster sampling is at work here: you first divide the population into natural groups, or clusters, then randomly select some of those clusters, and survey everyone within the chosen clusters. This approach is efficient for large or spread-out populations because you only have to collect data from entire groups rather than individuals scattered everywhere, while keeping a random element at the cluster level. It works well when clusters fairly represent the whole population, though you need enough clusters to balance potential similarity among members within the same cluster. The other methods described—convenience sampling (easy to reach), self-selecting sampling (volunteers), and purposive sampling (targeted groups)—do not involve randomly selecting clusters and surveying all members inside them, which is why cluster sampling is distinct.