What is an example of Stratified Random Sampling?
A stratified sample is one taken intentionally and specifically from a subset of the larger population with a common characteristic. Sampling should be random in any case for statistical validity.
A stratified sample is taken when you only want to observe possible correlations in one variable within a specific group. For example, political party affiliation can be sampled across a population. But if you want to know whether there are differences in affiliation based on age you would “stratify” the sample into specific age groups.
Care must be taken with stratified sample results so that they are not later erroneously interpreted as general population statistics. Similarly, the sampling must be taken in a random manner to avoid additional bias in interpretation.
"Randomization” is most often done by taking samples from locations or times selected by random number generators.