Which sampling method involves selecting entire groups, or clusters, and including all members from the chosen clusters?

Which sampling method involves selecting entire groups, or clusters, and including all members from the chosen clusters?

• A. Cluster sampling
• B. Systematic sampling
• C. Stratified sampling
• D. Simple random sampling

Answer: (A)

Cluster sampling divides the population into natural groups, called clusters, and then randomly selects some of those clusters. After choosing the clusters, you include every member from each selected cluster in the sample. This approach is efficient when it’s easier to collect data by group rather than by individuals scattered across the whole population. This differs from systematic sampling, which picks every kth person from a list; from stratified sampling, which samples from each subgroup rather than taking all members of whole groups; and from simple random sampling, which selects individuals randomly from the entire population without regard to grouping. For example, surveying all students in randomly chosen schools (clusters) rather than selecting individuals from across all schools embodies cluster sampling.

Cluster sampling divides the population into natural groups, called clusters, and then randomly selects some of those clusters. After choosing the clusters, you include every member from each selected cluster in the sample. This approach is efficient when it’s easier to collect data by group rather than by individuals scattered across the whole population.

This differs from systematic sampling, which picks every kth person from a list; from stratified sampling, which samples from each subgroup rather than taking all members of whole groups; and from simple random sampling, which selects individuals randomly from the entire population without regard to grouping. For example, surveying all students in randomly chosen schools (clusters) rather than selecting individuals from across all schools embodies cluster sampling.