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Stratified sampling divides a population into distinct groups (strata) and selects samples from each group proportionally. In this example, departments act as strata, and employees are randomly chosen within each group. This method ensures representation from all departments, reducing sampling bias. Stratified sampling is particularly useful when population groups differ significantly, as it enhances the reliability of results. Why Other Options Are Wrong :
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