In which sampling design are subjects grouped into strata and then drawn randomly from each group?

In which sampling design are subjects grouped into strata and then drawn randomly from each group?

• A. Stratified Random Sample
• B. Cluster Random Sample
• C. Purposive Sample
• D. Quota Sample

Answer: (A)

Stratified random sampling divides the population into subgroups that share a characteristic (strata) and then draws random samples from each stratum. This ensures representation from every subgroup and tends to increase precision by reducing variability within each subgroup, since comparisons can be made with proportional or equal representation across groups. This design differs from others in that it relies on random selection inside every stratum, which preserves probability-based sampling within each subgroup. In cluster sampling, you first pick whole clusters and then sample within those clusters, which doesn’t guarantee representation from each subgroup. Purposive sampling involves selecting units based on researcher judgment rather than randomly, and quota sampling fills preset subgroup quotas but selects within those quotas nonrandomly.

Stratified random sampling divides the population into subgroups that share a characteristic (strata) and then draws random samples from each stratum. This ensures representation from every subgroup and tends to increase precision by reducing variability within each subgroup, since comparisons can be made with proportional or equal representation across groups.

This design differs from others in that it relies on random selection inside every stratum, which preserves probability-based sampling within each subgroup. In cluster sampling, you first pick whole clusters and then sample within those clusters, which doesn’t guarantee representation from each subgroup. Purposive sampling involves selecting units based on researcher judgment rather than randomly, and quota sampling fills preset subgroup quotas but selects within those quotas nonrandomly.