When a subgroup has a low frequency within the population, which sampling approach helps ensure representation?

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

Answer: (A)

When a subgroup is small in the population, you want to guarantee its presence in the sample. Stratified sampling achieves this by dividing the population into meaningful subgroups (strata) and drawing samples from each one. If you allocate samples proportionally to each stratum’s size, every subgroup is represented in the final sample in the same proportion as in the population. You can also sample a fixed number from each stratum to ensure even rare groups are included, which improves the precision of comparisons across groups.

This approach helps prevent underrepresentation that can happen with methods that pick individuals at random from the whole population without regard to subgroup size. In contrast, simple random sampling can yield too few members from low-frequency subgroups, systematic sampling depends on the order of the list and may still miss small groups, and convenience sampling tends to bias toward easily reachable individuals and overlook less common subgroups.