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What is the main difference between a Cluster Sample and a Stratified Random Sample?

A. A Stratified Random Sample contains groups selected for convenience, but a Cluster Sample uses groups that have some characteristic in common.
B. A Cluster Sample contains groups selected for convenience, but a Stratified Random Sample uses groups that have some characteristic in common.

Sagot :

GinnyAnswer

Final answer:

Cluster samples involve selecting entire clusters, whereas stratified random samples ensure representation from each stratum.


Explanation:

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.


Learn more about Sampling Methods here:

https://brainly.com/question/12902833


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