What is the primary purpose of stratified sampling in research?

The primary purpose of stratified sampling in research is to divide the population into distinct subgroups or strata based on specific characteristics that are relevant to the research. This method ensures that each subgroup is represented proportionately in the sample, which can lead to more accurate and generalizable results. By recognizing the diversity within a population, researchers can capture the variations that might exist among different groups, such as age, gender, income, or educational level. This approach helps in reducing sampling bias and enables more precise comparisons and analyses within the context of the study.

While random selection is important in ensuring the representative nature of a sample, stratified sampling specifically focuses on the proportional representation of different subgroups. Analyzing communication content and enhancing credibility may be relevant to certain aspects of research, but they do not specifically highlight the unique value offered by stratified sampling in terms of subgroup proportion and representation.