What is the purpose of stratified sampling?

• A. Deliberately choosing which bits to sample to ensure coverage of all areas based on prior knowledge
• B. To speed up data collection
• C. To avoid needing prior knowledge
• D. To maximize randomness

Answer: (A)

Stratified sampling is used to ensure the sample represents all the different parts of a population. You divide the area into strata that are distinct but collectively cover the whole area (for example, urban vs. rural, or different land-use types) and then take samples from each stratum, usually with random selection within each one. This deliberate approach relies on knowledge of how the population varies, so the final results reflect all areas rather than just one part. It isn’t primarily about speeding up data collection, it does require prior knowledge to set up the strata, and while randomness is used within strata, the main aim is coverage and representativeness across all areas.