Read, more elaboration about it is given here. Similarly, what is meant by stratified sampling?
Stratified sampling refers to a type of sampling method . With stratified sampling, the researcher divides the population into separate groups, called strata. Then, a probability sample (often a simple random sample ) is drawn from each group. Stratified sampling has several advantages over simple random sampling.
Secondly, what is an example of a cluster sample? The most common cluster used in research is a geographical cluster. For example, a researcher wants to survey academic performance of high school students in Spain. He can divide the entire population (population of Spain) into different clusters (cities).
Furthermore, how do you calculate a stratified sample?
Step 1: Divide the population into smaller subgroups, or strata, based on the members' shared attributes and characteristics. Step 2: Take a random sample from each stratum in a number that is proportional to the size of the stratum. Step 3: Pool the subsets of the strata together to form a random sample.
How do you determine sample size in stratified sampling?
The sample size for each strata (layer) is proportional to the size of the layer: Sample size of the strata = size of entire sample / population size * layer size.