Surveys can be classified as probabilistic sampling:
• Simple random sampling: If you have a relatively small, self-contained, or clearly stated population, such as a city, you might simply obtain a list of the entire population and then randomly select individuals from the list to answer a survey.
• Stratified random sampling: Whenever you want to ensure the population reflects the known demographics or distributional characteristics of the source population, you might need to stratify your sample, making sure that you over sample small cohorts of the population to get significant results for smaller groups.
• Systematic random sampling: If you have a large list of members of a source population, you might choose to select every 10th or 100th individual. As long you have a fixed sampling interval, this is the same as random sampling.
• Cluster (area) random sampling: If you had population clusters, you could sample from each one or randomly select a few clusters and sample from them. This is termed as multi-stage sampling, which refers generally to any mixing of sampling methods.