Non-probability sampling is a technique where the likelihood of selecting any individual from the target population is neither known nor calculable. While this approach is often more cost-effective and faster than probability sampling, it can introduce selection, response, and measurement biases, limiting how well the results can be applied to a broader population.

Sampling Techniques

One standard method is convenience sampling, where participants are chosen based on their accessibility. For example, a study on dietary habits might survey people at a local gym, focusing on readily available people.

Judgmental or purposive sampling involves selecting participants based on specific characteristics or expertise. For example, experienced marathon runners would be chosen to evaluate the effectiveness of a new sports drink.

Quota sampling ensures that specific subgroups are represented in the sample according to predetermined quotas. For instance, in a study on urban transportation preferences, researchers might ensure that their sample includes a certain percentage of cyclists, drivers, and public transit users to reflect the population distribution.

Snowball sampling relies on initial participants to recruit others from their networks, making it particularly useful for studying hard-to-reach or specialized populations. This method might be used in research on underground music scenes, where initial interviewees refer to other musicians and fans.