Ace the Social Work Education Exam 2026 – Empower Your Future, One Question at a Time!

Random sampling uses probability theory to aim for a sample that reflects the population it comes from. Because every member has a known chance of selection, the sample’s characteristics can serve as unbiased estimates of the population’s characteristics, allowing findings to be generalized to that population. This generalization is appropriate for the population from which the sample was drawn, not to any population in general. The method matters—nonrandom approaches undermine external validity, so generalization depends on the sampling procedure being truly random. While larger samples reduce sampling error and improve precision, the ability to generalize rests primarily on how the sample was selected rather than on size alone.