under what circumstances stratified sampling is considered?
Answers
Answer:
Stratified sampling involves dividing the population into various groups or classes known as strata and then randomly choosing a specified number of objects from each stratum in order to obtain a sample that represents the population.
The condition for employing stratified sampling is that the population is heterogeneous in nature.
We should be able to clearly form sub-groups in the population based on some criteria.
Ideally, each member of the population must be a part of one and only one stratum. Only then will the resulting sample will fulfil the conditions of probability sampling.
Answer:
Stratified random sampling is appropriate whenever there is heterogeneity in a population that can be classified with ancillary information; the more distinct the strata, the higher the gains in precision. The same population can be stratified multiple times simultaneously.