## 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.

**Disadvantages:**

- 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.

## Conclusion

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.

## References