A company divides its employees into departments (e.g.,

Solution

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 :

• A) Cluster sampling would involve selecting entire departments as samples, not individuals.
• B) Systematic sampling involves a fixed interval, such as every 5th employee, irrespective of department.
• C) Simple random sampling doesn’t consider strata or groups.
• E) Convenience sampling would select individuals based on accessibility, not group representation.