Learn more about different types of probability and non-probability sampling methods.
There are two types of sampling methods: probability and non-probability. In probability samples, you know how likely it is that an individual in the population is chosen for your sample. Probability samples allow you to draw conclusions about the extent to which the parameters you measured differ from the population, because your sample will be representative of the population you want to investigate. In non-probability samples, you do not know the chances of people being selected for your sample. Yet, this sampling method yields the advantages of being faster and more cost-effective.
Examples of probability sampling methods:
- Simple random sampling. Simple random sampling means that every member of the target population has an equal chance to be selected for the study. In other words, respondents are chosen completely at random.
- Stratified random sampling. In stratified samples, the population is divided into groups, based on certain characteristics (e.g., age and gender). Within each group, a probability sample (often a simple random sample) is selected. In stratified sampling, the groups are called strata.
- Systematic random sampling. When using this sampling method, a list containing every member in the population of interest is created. From this list, the first x elements are chosen. Thereafter, every xth element in the list is chosen. Note that this sampling method differs from simple random sampling in that not every element in the population is equally likely to be selected for the sample.
Examples of non-probability sampling methods:
- Convenience Sampling. Convenience sampling means collecting a sample of whichever participants are easiest to reach. It’s a first come, first serve sample.
- Quota Sampling. This method is similar to stratified sampling: the population is divided into groups, based certain characteristics. Within each group, a non-probabilistic sample (often a convenience sample) is selected.
- Purposive Sampling. In this sampling method, individuals are hand-selected to be part of a sample. This might be because the individual's views are considered to be particularly important or representative of the population under investigation.