midStatistics
What is stratified sampling and when should it be used?
Updated May 17, 2026
Short answer
Stratified sampling divides population into subgroups and samples from each.
Deep explanation
It ensures representation of all subgroups (strata) by sampling proportionally or equally from each. This reduces variance and improves representativeness compared to simple random sampling.
Real-world example
Election polling ensures representation of age groups, genders, and regions.
Common mistakes
- Using stratification without knowing population structure.
Follow-up questions
- What is proportional stratified sampling?
- What is variance reduction benefit?