Which sampling method requires representation from each stratum by drawing random samples from every stratum?

Which sampling method requires representation from each stratum by drawing random samples from every stratum?

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

Answer: (C)

Stratified sampling is designed to ensure representation from every subgroup by dividing the population into strata based on a characteristic and then drawing random samples from each stratum. This guarantees that each stratum contributes to the overall sample, capturing differences across groups and providing more precise estimates when those groups differ on the variable of interest. By comparison, systematic sampling selects units at regular intervals from an ordered list and doesn’t inherently ensure every stratum is represented. Simple random sampling chooses from the entire population without guaranteeing coverage of all strata, so some groups may be underrepresented or missing. Cluster sampling groups units into clusters and samples whole clusters, which can miss some strata entirely if they don’t align with the chosen clusters.

Stratified sampling is designed to ensure representation from every subgroup by dividing the population into strata based on a characteristic and then drawing random samples from each stratum. This guarantees that each stratum contributes to the overall sample, capturing differences across groups and providing more precise estimates when those groups differ on the variable of interest.

By comparison, systematic sampling selects units at regular intervals from an ordered list and doesn’t inherently ensure every stratum is represented. Simple random sampling chooses from the entire population without guaranteeing coverage of all strata, so some groups may be underrepresented or missing. Cluster sampling groups units into clusters and samples whole clusters, which can miss some strata entirely if they don’t align with the chosen clusters.