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Cluster sampling

Cluster sampling randomly selects entire groups from a population, then surveys units within those groups. It cuts costs for dispersed populations but sacrifices precision because units within a cluster tend to be similar to one another.

ByHoang TruongUpdated

FrameworkSampling design

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Cluster sampling selects entire groups — school classes, branches, census blocks — at random, then surveys the units inside them, which is far cheaper than reaching scattered individuals across a dispersed population. Simple random sampling instead draws individual units directly. Because units within a cluster tend to resemble each other, cluster sampling loses precision compared with a simple random sample of the same size, trading statistical efficiency for lower cost.

Where it fits
TopicFoundations: Data, Populations & SamplingAdvancedSubjectData Analysis & StatisticsAdvanced

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PracticeCORE

A researcher studying employee wellbeing at a nationwide supermarket chain randomly selects 20 branches and surveys every employee within those branches. What sampling method is this, and what is its primary statistical limitation?

Select an answer to check your understanding.