Convenience sampling is a non-probability sampling technique. Subjects are selected for a study by the convenience of their availability to the researcher. Convenience could be based on a number of factors, including geographic location or personal relationship with the researcher. The advantage of this technique is that it can be fast and inexpensive. However, as there is no way to know how a convenience sample relates to the larger population, it is not very useful for generalizing information about the entire population.
Quota sampling is a technique which keeps the percentage of key traits in the sample subjects proportionate to that of the entire population. This is a non-probability sampling technique. Quota sampling is useful when studying a specific subgroup, or the interactions between subgroups, in a given population. On the other hand, while it seems that a quota sample would be highly representative of a population, this can be misleading. Only the selected key traits are held in proportion to the larger population, and as a result, other important traits may be over- or underrepresented in the sample.
Voluntary sampling is a form of non-probability sampling in which subjects select themselves for inclusion in the study. This can be an easy and inexpensive sampling method. Unfortunately, the researcher has minimal control over the sample subjects. Also, the sample could be misleading, over-representing the more motivated extremes of the population and under-representing moderate or less passionate members.
Snowball sampling is another non-probability sampling method. An initial subject provides referrals or directions to other potential subjects, who then lead to still more subjects. This technique is useful when studying small, isolated or rare populations. The researcher, though, has little control over the subject pool and referred subjects may not be representative of the entire population.
A simple random sample is a sample selected by random chance from the known, finite population. As all possible combinations of sample subjects are equally likely, this is a probability sampling technique. This sampling method is beneficial in removing selection biases and achieving results that can be generalized to the entire population.
Systematic sampling is another type of probability sampling. Unlike random sampling, subjects are chosen using a defined systematic method rather than random chance. In a systematic sampling method, every nth member of a population is chosen, starting with a randomly selected first subject. This method, like other probability sampling techniques, has the benefit of removing selection biases and achieving representative results. The downfall is that the entire population must be known before subjects are selected.