Stratification refers to dividing a population into groups, called strata, such that pairs of population units within the same stratum are deemed more similar (homogeneous) than pairs from different strata. The strata are mutually exclusive (non-overlapping) and exhaustive of the population. Clearly sufficient information on each population unit must be available before we can divide the population into strata.
The primary reason for dividing a population into strata is to make use of the strata in drawing a sample. For example, instead of drawing a simple random sample of sample size n from the population, one may draw a simple random sample of sample size n h from stratum h of L strata, where \(n = {n}_{1} + \cdots + {n}_{L}.\) The sample selection for any stratum is done independently of the other strata. The stratum sample sizes n h are often chosen proportional to the number of population units in stratum hbut other allocations of the stratum samples may be preferred in specific...
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Cohen, M.P. (2011). Stratified Sampling. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_574
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