National Counselor Exam (NCE)

Stratified sampling is the technique that purposefully divides the population into distinct subgroups or strata, such as age, gender, income level, etc., before randomly selecting participants from each subgroup. This method ensures that each subgroup is adequately represented in the sample, which is especially important when the characteristics of those subgroups are believed to affect the outcomes of the study.

By using stratified sampling, researchers can enhance the precision of their estimates and provide more reliable conclusions about the population. This contrasts with other sampling methods, which may not account for the diversity within the population or might over-represent certain groups. For example, cluster sampling involves randomly selecting entire clusters or groups but does not specifically require representation across the various strata of the population, potentially leading to underrepresentation of some segments. Simplified sampling is not a standard term in research methodology, and randomized control sampling mainly refers to the method used in clinical trials to assign participants to different groups, rather than focusing on representation.