Stratified sampling involves?

• A. Selecting a random cluster only
• B. Convenience sampling
• C. Entire population surveyed
• D. Dividing the population into subgroups and sampling from each subgroup in proportion to the population

Answer: (D)

Stratified sampling focuses on representing different subgroups within a population. The idea is to divide the whole group into strata—subgroups that share a characteristic, like grade level, age, or gender—and then sample from each stratum in the same proportion as it appears in the population. This keeps the overall sample’s makeup similar to the real population, which reduces bias and leads to more accurate overall estimates. For example, if a school has 40% freshmen and 60% sophomores, you’d sample so that about 40% of your sample are freshmen and 60% are sophomores.

This differs from choosing only from random clusters, which focuses on entire groups rather than proportional representation of all subgroups. It also differs from convenience sampling, which picks the easiest people to reach and can be biased. And it’s not a census, where every member of the population is surveyed.