What is an advantage of stratified sampling?

The advantage of stratified sampling lies in its ability to ensure random selection from identified strata. This sampling method involves dividing the population into distinct subgroups or strata, which possess similar characteristics, and then randomly selecting samples from each of these groups. By doing so, stratified sampling aims to achieve a more representative sample overall while also allowing researchers to make comparisons between different strata within the population.

This process improves the precision of estimates regarding the population characteristics, as it reduces sampling error. It is particularly useful when certain subgroups within a population are small or need to be specifically represented, ensuring that the research findings reflect the diverse perspectives and traits of the entire population. This contributes to the validity and reliability of the study's outcomes, making stratified sampling a robust choice in survey research and various experimental designs.