In stratified sampling, researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment, etc). Once divided, each subgroup is randomly sampled using another probability sampling method.

What is an example of stratified sampling?

Age, socioeconomic divisions, nationality, religion, educational achievements and other such classifications fall under stratified random sampling. Let's consider a situation where a research team is seeking opinions about religion amongst various age groups.

How do you do stratified sampling?

To create a stratified random sample, there are seven steps: (a) defining the population; (b) choosing the relevant stratification; (c) listing the population; (d) listing the population according to the chosen stratification; (e) choosing your sample size; (f) calculating a proportionate stratification; and (g) using ...