Which method involves taking a sample from different groups to ensure representation?

Stratified sampling is a method that involves dividing a population into distinct subgroups, or strata, that share specific characteristics, such as age, gender, or socioeconomic status. By ensuring that each group is represented in the sample proportionally, stratified sampling enhances the representativeness of the data collected. This method allows researchers to obtain more precise estimates and insights about the overall population, as it acknowledges the diversity within that population and aims to include that diversity in the sample.

For instance, if a researcher is conducting a survey on educational outcomes, they may divide the population into different strata based on grade levels or demographic factors. By sampling from each of these groups, the researcher can ensure that the findings reflect the experiences of all segments of the population.

This approach contrasts with methods like convenience sampling, where samples are taken from easily accessible populations without considerations for broader representation. Likewise, quota sampling involves specifying a certain number of subjects from each subgroup, but it may not adequately reflect the proportions in the overall population. Systematic sampling, on the other hand, involves selecting every nth individual from a list, which does not account for subgroup representation.