What distinguishes probability sampling from non-probability sampling?

The distinction between probability sampling and non-probability sampling primarily lies in the ability to generalize findings to a broader population. Probability sampling involves random selection methods that give each individual in the population a known and non-zero chance of being selected. This process allows researchers to make statistical inferences about the entire population based on the sample. Hence, results from a probability sample can be generalized to the population, lending greater validity to the research findings.

In contrast, non-probability sampling lacks this element of randomness, meaning that not all individuals have a fair chance of being selected. As a result, the findings from non-probability samples cannot be reliably generalized to the overall population, which can limit their applicability and the conclusions drawn from them.

Overall, the ability to generalize findings based on sampling method directly influences how researchers interpret their results and make decisions based on their data.