Stratified sampling: Difference between revisions
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When subpopulations of the population to be studied vary considerably, it is advantageous to sample each subpopulation (stratum) independently and produce a [[Weighted Mean]] that has less variability than the [[Arithmetic Mean]] of a random sample. There are several possible strategies: |
When subpopulations of the population to be studied vary considerably, it is advantageous to sample each subpopulation (stratum) independently and produce a [[Weighted Mean]] that has less variability than the [[Arithmetic Mean]] of a random sample. There are several possible strategies: |
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Revision as of 12:08, 29 June 2001
When subpopulations of the population to be studied vary considerably, it is advantageous to sample each subpopulation (stratum) independently and produce a Weighted Mean that has less variability than the Arithmetic Mean of a random sample. There are several possible strategies:
- Proportionate allocation uses the same Sampling Fraction in each of the strata.
- Optimum allocation takes larger samples in the strata with the greatest variability to generate the least possible sampling variance.
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