In cluster sampling, a random subset of clusters is chosen and all members in those clusters are surveyed.

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Multiple Choice

In cluster sampling, a random subset of clusters is chosen and all members in those clusters are surveyed.

Explanation:
Cluster sampling groups the population into naturally occurring clusters, then you randomly pick some clusters and survey everyone in those chosen clusters. This matches the described process: a random subset of clusters is selected and all members within those clusters are surveyed. It helps save time and resources by focusing data collection on whole clusters rather than individuals scattered across every cluster. This approach is different from simple random sampling, where every individual would have an equal chance of being selected from the entire population; it’s also different from surveying every cluster (a census) and from sampling only one cluster (which would ignore most of the population).

Cluster sampling groups the population into naturally occurring clusters, then you randomly pick some clusters and survey everyone in those chosen clusters. This matches the described process: a random subset of clusters is selected and all members within those clusters are surveyed. It helps save time and resources by focusing data collection on whole clusters rather than individuals scattered across every cluster. This approach is different from simple random sampling, where every individual would have an equal chance of being selected from the entire population; it’s also different from surveying every cluster (a census) and from sampling only one cluster (which would ignore most of the population).

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