This question relates to stratified probability sampling. If one has 1,000 recor

Question

This question relates to stratified probability sampling. If one has 1,000 records and divides those records into 12 different strata, or groups, why does picking a random start, and then picking every 5th record end up giving one strata sample sizes that are proportional to the relative sizes of the strata in the sample frame? I can do this with a data set, so that is not the issue. I am asking for a written explanation of why it works (I am having difficulty articulating the reasoning behind it).

Explanation / Answer

See, before you make any groups on any variable you sort it by ascending or descending order. This sorting remains the major key for the reason behind stratified sampling.Now after this step if you chose observations at regular interval if you start from any random observation will make the whole sample stratified according to the particular variable or set of variables you want to stratify the sample.

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