In stratified sampling, researchers divide the population into subgroups (strata) based on shared characteristics. Random samples are then drawn from each stratum, ensuring representation of all population segments. This method enhances accuracy by reducing sampling error and provides more precise estimates. While implementation can be complex and requires knowledge of population stratification, stratified sampling is widely used in market research, public opinion polls, and biological research, offering increased accuracy and statistical inference reliability.