Which of the following best describes stratified sampling?

Stratified sampling is best described as a method that divides the population into subgroups before sampling. This approach is used to ensure that specific segments of a population are adequately represented in the sample, which enhances the reliability and validity of the research findings. By creating strata or subgroups based on characteristics such as age, gender, income, or education level, researchers can ensure that each subgroup's unique perspectives and experiences contribute to the overall data collected.

This method contrasts with the other options, which do not accurately capture the essence of stratified sampling. For instance, selecting participants randomly from the entire population does not involve grouping into subcategories and does not ensure that specific segments are adequately represented. Convenience sampling focuses on selecting individuals who are easiest to reach, often leading to biased results that do not reflect the broader population. Lastly, while aiming for equal representation across demographics in sampling is important, simply requiring it does not constitute the systematic approach of dividing the population into strata first, which is central to stratified sampling.