Stratified sampling

A beacon of methodical fairness, stratified sampling is a technique employed to select a representative sample from a population by first dividing the population into distinct, non-overlapping strata, or groups, based on shared characteristics, and then drawing random samples from each stratum, ensuring a more accurate reflection of the population's diversity.

Example

A financial analyst studying the performance of companies across various industries might employ stratified sampling to ensure that their sample accurately represents the entire market. They would first divide the companies into strata based on industry sectors, such as technology, healthcare, and finance. Then, they would randomly select companies from each stratum to include in their sample. This method helps to achieve a more balanced and representative sample, enabling the analyst to draw more reliable conclusions about the overall market performance and trends.