What is a Non-Probability Sample?
A non-probability sample is a sampling method used in research that does not rely on random selection to obtain participants. In other words, the individuals who are chosen to be a part of the sample are not chosen by chance. Non-probability sampling is sometimes referred to as non-random sampling.
Types of Non-Probability Sampling
Non-probability sampling consists of several types, including:
- Convenience sampling: involves selecting participants who are conveniently available, such as those in the same area or those who agree to take part in the study.
- Purposive sampling: involves selecting participants based on specific criteria, such as those with a certain level of education or those with a certain type of experience.
- Quota sampling: involves selecting participants based on predetermined quotas, such as selecting a certain number of people from a certain age group or selecting a certain number of people from a certain race.
- Snowball sampling: involves asking existing participants to refer other potential participants to the study.
- Expert sampling: involves selecting participants who have expertise in the area of study.
Advantages and Disadvantages of Non-Probability Sampling
Non-probability sampling has both advantages and disadvantages. Advantages:
- It is often faster and more cost effective than probability sampling.
- It is useful for exploratory research.
- It can provide access to participants who may not be available through probability sampling.
- It can be difficult to generalize the results to a larger population.
- It is more susceptible to researcher bias.
- It can be difficult to determine the representativeness of the sample.
Non-probability sampling is a useful method for certain types of research, but it is important to understand the advantages and disadvantages before using it.
Non-probability sampling is a common research method used to obtain participants for a study. It has several advantages and disadvantages, and it is important to consider these before using this type of sampling.