What is the purpose of stratified sampling?

Stratified sampling is a method used in research to ensure that specific subgroups within a population are adequately represented in the sample. The primary purpose of this approach is to divide the population into different strata, or categories, based on certain characteristics (such as age, gender, income level, etc.) that are relevant to the research being conducted. By sampling from these distinct groups, researchers can achieve a more representative sample that reflects the diversity of the entire population.

This is particularly valuable in studies where certain subgroups might be underrepresented or where differences among these groups are expected to significantly influence the research outcomes. For instance, if a researcher were studying consumer preferences between different income brackets, stratified sampling would allow them to capture the varied perspectives of both higher and lower-income individuals, ensuring comprehensive data collection.

In contrast, the other options, while related to sampling techniques, do not capture the essence of stratified sampling as effectively. For instance, eliminating bias is a general goal of various sampling methods, not exclusive to stratified sampling. Ensuring equal chance of selection also pertains more to random sampling techniques. Assessing overall satisfaction relates more to the goal of the research rather than the sampling method used. Therefore, the choice emphasizing the division of a population into