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A variety of sampling strategies are available in cases when setting or context create restrictions. For example, stratified sampling is used when the population's characteristics such as ethnicity or gender are related to the outcome or dependent variables being studied. Simple random sampling, in contrast, is used when there is no regard for strata or defining characteristics of the population from which the sample is drawn. The assumption is that the differences in these characteristics are normally distributed across all potential participants.

Cluster sampling is the selection of units of natural groupings rather than individuals. For example, in marketing research, the question at hand might be how adolescents react to a particular brand of chewing gum. The researcher may access such a population through traditional channels ...

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