Stratification is sometimes launched once the sampling period in a procedure identified as "poststratification".[3] This technique is often applied due to a lack of prior expertise in an proper stratifying variable or once the experimenter lacks the necessary information to produce a stratifying variable during the sampling stage.
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In lots of situations the sample portion may be diversified by stratum and knowledge will have to be weighted to properly represent the population. Thus for example, a simple random sample of people in the United Kingdom may not involve some in distant Scottish islands who would be inordinately expensive to sample.
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Clustering can lessen vacation and administrative expenditures. During the example previously mentioned, an interviewer may make an individual trip to visit many homes in a single block, rather than being forced to drive to a unique block for every house.
At times what defines a population is obvious. For example, a manufacturer wants to choose whether or not a batch of fabric from production is of high adequate high quality to generally be introduced to the customer, or needs to be sentenced for scrap or rework resulting from inadequate high quality. In such a case, the batch could be the inhabitants.
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Lastly, in some instances (for instance types with a lot of strata, or those by using a specified minimum amount sample sizing per group), stratified sampling can likely need a greater sample than would other techniques (although most often, the essential sample size will be no larger sized than might be essential for simple random sampling).
The textbook by Groves et alia delivers an overview of study this methodology, including current literature on questionnaire development (educated by cognitive psychology) :