answersLogoWhite

0

Basically in a stratified sampling procedure, the population is first partitioned into disjoint classes (the strata) which together are exhaustive. Thus each population element should be within one and only one stratum. Then a simple random sample is taken from each stratum, the sampling effort may either be a proportional allocation (each simple random sample would contain an amount of variates from a stratum which is proportional to the size of that stratum) or according to optimal allocation, where the target is to have a final sample with the minimum variabilty possible. The main difference between stratified and cluster sampling is that in stratified sampling all the strata need to be sampled. In cluster sampling one proceeds by first selecting a number of clusters at random and then sampling each cluster or conduct a census of each cluster. But usually not all clusters would be included.

User Avatar

Wiki User

15y ago

Still curious? Ask our experts.

Chat with our AI personalities

RafaRafa
There's no fun in playing it safe. Why not try something a little unhinged?
Chat with Rafa
CoachCoach
Success isn't just about winning—it's about vision, patience, and playing the long game.
Chat with Coach
TaigaTaiga
Every great hero faces trials, and you—yes, YOU—are no exception!
Chat with Taiga

Add your answer:

Earn +20 pts
Q: What is the difference between stratified random sampling and cluster sampling?
Write your answer...
Submit
Still have questions?
magnify glass
imp