A non-probability sample is a sampling technique used in research and survey studies where the selection of individuals or units for the sample does not follow a random or probability-based approach. In non-probability sampling, the chance of any particular member of the population being included in the sample is unknown and may be subjective or based on convenience.
Here are some common types of non-probability sampling methods:
1. Convenience Sampling: Convenience sampling involves selecting individuals or units that are readily available and convenient to the researcher. This method often leads to a sample that is easy to access but may not be representative of the entire population.
2. Purposive Sampling: Purposive sampling involves selecting individuals or units based on specific criteria or characteristics relevant to the research objectives. The researcher uses their judgment to handpick participants who are likely to provide valuable insights or represent a particular group of interest.
3. Snowball Sampling: Snowball sampling relies on existing participants to refer or nominate additional individuals who meet the criteria for the study. This sampling method is often used when the population of interest is difficult to identify or reach through traditional sampling techniques.
4. Quota Sampling: Quota sampling involves selecting individuals or units based on pre-determined quotas or proportions that reflect specific characteristics or demographics of the population. The researcher selects participants to fulfill certain criteria until the quotas are met, without random selection.
Non-probability sampling methods are more commonly used in exploratory research, qualitative studies, or situations where it is difficult or impractical to implement probability sampling techniques. However, it is important to note that non-probability samples are generally less representative of the population compared to probability samples. Therefore, the findings from non-probability samples may have limitations in terms of generalizability and the ability to make statistical inferences about the population.
