In stratified random sampling for a national nutrition survey, the country is divided into urban/rural strata and samples are drawn proportional to strata size. Compared to simple random sampling, this method:

• A Reduces variance of the estimate by ensuring representation of each stratum ✓
• B Increases sampling error by introducing strata boundaries
• C Is less efficient because it requires knowledge of population strata
• D Introduces systematic bias identical to cluster sampling

Explanation

Stratified random sampling reduces sampling variance (increases precision) by homogenising within-stratum variation; each stratum contributes its estimate independently, and the overall variance is a weighted sum of stratum variances — which is smaller than population variance. The requirement for prior knowledge of strata is a logistical cost but does not make it less efficient statistically. It is distinct from cluster sampling, which groups units geographically and can increase variance.

Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.

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