Cluster sampling chooses groups of observational units, such as production days, rather than dispersed individual units. Testing every unit in a selected group is a one-stage cluster sample. Positive within-cluster intraclass correlation reduces the information supplied by a fixed number of sampled units, although collecting clustered observations can be cheaper.
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