Stratified random sampling is used when we have subgroups in our population that are likely to differ substantially in their responses or behavior. This sampling technique treats the population as though it were two or more separate populations and then randomly samples within each.

For example, you are interested in visual-spatial reasoning and previous research suggests that men and women will perform differently on these types of task. So, you divide your sample into male and female members and randomly select equal numbers within each subgroup (or "stratum"). With this technique, you are guaranteed to have enough of each subgroup for meaningful analysis.