Stratified random sampling is a method used in statistics to ensure that different subgroups within a population are represented in a sample. In this approach, the population is divided into distinct strata based on specific characteristics, such as age, gender, or income level. Researchers then randomly select samples from each stratum, which helps to capture the diversity of the entire population. This technique improves the accuracy and reliability of survey results by reducing sampling bias. By ensuring that each subgroup is adequately represented, stratified random sampling allows for more precise comparisons and insights about the population as a whole.