American Institute of Certified Planners (AICP) Practice Exam

Stratified sampling is best used when:

1. Population has similar characteristics

2. Population may have multiple groups

3. Sample needs to be large

4. Individuals are selected randomly

The correct answer is: Population may have multiple groups

Stratified sampling is most effectively employed when the population can be divided into distinct subgroups or strata that may differ in important ways. This method ensures that each subgroup is appropriately represented in the sample, thus allowing for more accurate and reliable estimates for each segment of the population. For instance, if a study aims to gather information on community opinions regarding a new policy, it would be beneficial to stratify the population based on demographic factors such as age, income, or education level. By ensuring that each stratum is represented, stratified sampling enhances the precision of the survey's results by minimizing sampling bias related to the characteristics of the subgroups. The other options do not accurately capture the essence of stratified sampling. While having similar characteristics within a population might lend itself to other sampling methods, stratified sampling thrives on the diversity among subgroups. Similarly, while achieving a large sample size can be important in research, it is not a definitive characteristic that warrants using stratified sampling; rather, the focus should be on representing the various strata within the population. Lastly, while random selection is a hallmark of creating a sample, in a stratified sample, it is often combined with dividing the population into strata before random sampling occurs within those groups—making it