The difference between a cluster sample and a stratified sample is: a) cluster samples use oversampling; stratified random samples are undersampling b) there is no difference between them c) cluster samples study all possible clusters; stratified random samples randomly select strata d) cluster samples use randomly selected clusters; stratified random samples use predetermined strata

Izabelle Lowery

Izabelle Lowery

Answered question

2022-10-23

The difference between a cluster sample and a stratified sample is:
a) cluster samples use oversampling; stratified random samples are undersampling
b) there is no difference between them
c) cluster samples study all possible clusters; stratified random samples randomly select strata
d) cluster samples use randomly selected clusters; stratified random samples use predetermined strata

Answer & Explanation

Dana Simmons

Dana Simmons

Beginner2022-10-24Added 14 answers

Cluster samples use randomly selected clusters; stratified random samples use predetermined strata.
Cluster sampling and stratified sampling are two types of probability random sampling methods. Both of them use random selection. But cluster samples divide population into clusters and select from it. But stratified data just select on the basis of predetermined strata.

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