Cluster samples involve selecting entire clusters, whereas stratified random samples ensure representation from each stratum.
Cluster Sample: Involves dividing the population into clusters and randomly selecting some clusters to include all members in those clusters. For example, selecting homeroom classes from a student population.
Stratified Random Sample: Involves dividing the population into strata and ensuring representation from each stratum. For instance, sampling students from each grade level.
Difference: A cluster sample includes entire clusters while a stratified random sample ensures representation from each stratum of the population.
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