Non-random Sampling Methods

Non-random sampling methods involve selecting individuals or items from a population based on non-random criteria. Unlike random sampling, these methods do not give every member of the population an equal chance of being selected. They are often quicker and easier to implement but may lead to biased results.

Quota Sampling

In quota sampling, researchers divide the population into subgroups (such as gender, age, or income) and select a sample that meets predefined quotas for each subgroup. However, the individuals within each subgroup are selected based on convenience rather than randomly.

Example: Interviewing 50 men and 50 women to meet a gender quota but choosing participants who are readily available.

Quota sampling ensures representation of subgroups, but it may introduce bias because of the non-random selection.

Opportunity (Convenience) Sampling

Opportunity sampling, also called convenience sampling, involves selecting individuals who are easiest to reach or most conveniently available.

Example: A researcher surveys people at a shopping mall because they are easily accessible.

This method is fast and inexpensive but can lead to biased results as the sample may not represent the broader population.