When is non-random sampling typically used?

Non-random sampling is typically employed when collecting a probability-based sample is impractical. In many research contexts, particularly when time, budget, or logistical constraints exist, researchers might find it challenging to randomly select participants from a larger population. Non-random sampling allows for the selection of subjects based on convenience or specific criteria, which can be crucial when quick results are needed or when the population is hard to access.

This approach can provide useful insights, particularly in exploratory research where the goal may be to gather preliminary data or to identify trends rather than to make generalizations about a larger population. Researchers may also use non-random sampling methods like convenience sampling, purposive sampling, or snowball sampling in situations where traditional random sampling would not yield feasible results. While this can introduce biases, it is often a necessary trade-off in practical research settings.