Just a note that "stratification" as described in this article is not what is traditionally meant by taking a stratified sample. The article states: > Stratifi

Just a note that "stratification" as described in this article is not what is traditionally meant by taking a stratified sample. The article states: > Stratification lowers variance by making sure that each sub-population is sampled according to its split in the overall population. In common practice, the main way that stratification lowers variance is by computing a separate estimate for each sub-population and then computing an overall population estimate from the sub-population estimates. If the sub-populations are more uniform ("homogeneous") than is the overall population, the sub-populations will have smaller variances than the overall population, and a combination of the smaller variances will be smaller than the overall population's variance. In short, you not only stratify the sample, but also correspondingly stratify the calculation of your wanted estimates. The article does not seem to take advantage of the second part. (P.S. This idea, taken to the limit, is what leads to importance sampling, where potentially every member of the population exists in its own stratum. Art Owen has a good introduction: https://artowen.su.domains/mc/Ch-var-is.pdf https://artowen.su.domains/mc/Ch-var-is.pdf.)