Foundations of Data Science
Stratified sampling is a sampling technique that involves dividing a population into distinct subgroups, known as strata, based on shared characteristics. This method ensures that each subgroup is adequately represented within the sample, which can lead to more accurate and reliable statistical inferences. By focusing on specific strata, researchers can reduce sampling bias and improve the precision of estimates compared to simple random sampling.
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