Stratified Random and Cluster Sampling by Ryan Backman

A sampling method where the population is separated into groups, typically geographically, and a random selection of clusters is made. Each individual in the cluster becomes part of the sample.

Smaller subgroups of the population, not necessarily similar in any way besides all being together in one place, making the individuals easier to sample together.

A random sampling method where individuals are separated into homogenous groups, then simple random samples are taken within each group.

The homogenous groups in a stratified random sample. All individuals in each stratum have something in common, and we would like to see how that affects the outcome of the sample.