What is a key difference between random sampling and non-random sampling?

The distinction between random and non-random sampling lies in how samples are selected from a population. Random sampling relies on chance, giving every individual an equal opportunity to be chosen, which minimizes selection bias and enhances representativeness. In contrast, non-random sampling does not ensure each member has an equal chance of selection and often involves judgment or convenience, leading to a higher risk of bias. Random sampling methods like simple random sampling or stratified sampling are thus preferred for studies requiring generalizable results, while non-random sampling is sometimes used for exploratory research where representativeness is less critical. The other options are incorrect because: • Option 1 confuses judgment with randomness; judgment sampling is a non-random method. • Option 2 reverses definitions, as random sampling, not non-random, ensures equal chance. • Option 3 is inaccurate; both sampling types are used in qualitative and quantitative research, depending on goals. • Option 5 is misleading, as time required varies by method specifics, not by randomness alone.