Which sampling method involves dividing the population into homogeneous subgroups and sampling from each subgroup using random selection within subgroups?

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Multiple Choice

Which sampling method involves dividing the population into homogeneous subgroups and sampling from each subgroup using random selection within subgroups?

Stratified sampling divides the population into homogeneous subgroups and then randomly samples from each subgroup. This approach ensures each subgroup is represented in the final sample, which improves precision when subgroups differ on the trait being measured. For example, if you’re studying attitudes across departments, you create a stratum for each department and randomly sample within each one. This differs from simple random sampling, which pulls from the entire population without regard to subgroups; cluster sampling groups people into clusters and samples entire clusters (or individuals within clusters) rather than guaranteeing representation from every subgroup; systematic sampling selects every kth person after a random start, which can miss important variation if there’s a pattern in the list.

Stratified sampling divides the population into homogeneous subgroups and then randomly samples from each subgroup. This approach ensures each subgroup is represented in the final sample, which improves precision when subgroups differ on the trait being measured. For example, if you’re studying attitudes across departments, you create a stratum for each department and randomly sample within each one. This differs from simple random sampling, which pulls from the entire population without regard to subgroups; cluster sampling groups people into clusters and samples entire clusters (or individuals within clusters) rather than guaranteeing representation from every subgroup; systematic sampling selects every kth person after a random start, which can miss important variation if there’s a pattern in the list.

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