ACCA Applied Knowledge · Management Accounting · Sampling methods
An auditor in a manufacturer's cost department wants to estimate average scrap per batch. Batches come from three plants of very different sizes and scrap rates. Which advantage makes stratified random sampling more suitable than simple random sampling?
Stratified random sampling ensures each plant is represented in proportion, which improves precision for a given sample size when groups differ markedly. It still needs a sampling frame and knowledge of the population, and it does not remove sampling error.
- AIt needs no information about the population
- BIt removes all sampling error
- CIt ensures each plant is represented, improving precision for a given sample sizeCorrect
- DIt is cheaper because no sampling frame is needed
Explanation
Stratified sampling divides the population into groups (here plants) and samples from each, so every group is represented and the estimate is usually more precise. It still needs a frame and population knowledge, and it does not eliminate sampling error.
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