A Level Sociology OCR Practice Exam 2026 – The All-in-One Guide to Exam Success!

Stratified sampling is best described as a method that weights subgroups by demographic characteristics. This technique is designed to ensure that various subgroups within a population are represented proportionately in the sample. In stratified sampling, the population is divided into distinct subgroups or strata based on specific characteristics such as age, gender, income, or education level.

Once these strata are identified, the researcher randomly selects participants from each group. This approach not only helps in obtaining a more representative sample but also allows researchers to make more accurate comparisons between different subgroups within the overall population.

This method contrasts with simple random sampling, which does not consider subgroup characteristics. By weighting these subgroups, stratified sampling enhances the validity and reliability of the research findings since it minimizes sampling bias and reflects the diversity within the population.