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Stratified sampling

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GPT 3.5
Stratified sampling is a sampling technique used in statistics to divide a population into smaller, more manageable subgroups called strata. In stratified sampling, the subgroups are created based on characteristics or variables that are important to the study. Each stratum is then sampled independently using a random sampling method, such as simple random sampling or systematic sampling. This technique ensures that each stratum is represented proportionally in the sample, which can help to reduce bias and increase the accuracy of statistical analysis. Stratified sampling is often used when the population is diverse and contains different subgroups, as it allows for more targeted and precise sampling within each subgroup.

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