<h2>Answer</h2>
Stratified sampling
<h2>Explanation</h2>
Stratified sampling is a process of dividing members of the population into homogeneous (separate) subgroups before sampling. Then a random sample is drawn from each group. Members in subgroups may not be fix and subgroups are created under specific type.
<h3>Example</h3>
Subgroup: Sophomore, Junior, Senior classes
This sampling technique increases the precision of sampling by reducing sample size especially when population size is too large.
In cluster sampling, a random subset of population is created and then random sample drawn from it. Members of all subgroups are equal.
In systematic sampling, fixed intervals from the larger population create the subset of population. Members of all subgroups are equal.
