Which sampling method is a non-probability approach where selection is based on the researcher's judgment?

Which sampling method is a non-probability approach where selection is based on the researcher's judgment?

• A. Purposive Sample
• B. Probability Sample
• C. Simple Random Sample
• D. Stratified Random Sample

Answer: (A)

Selecting participants based on the researcher's judgment for a specific purpose is purposive sampling. This non-probability approach focuses on choosing cases that are especially informative or representative of a phenomenon you want to study, such as individuals with particular experiences, expertise, or characteristics. The aim is depth and relevance rather than generalizability to the entire population. Because the researcher purposefully selects cases, not every member of the population has an equal chance of inclusion, and you can’t rely on statistical generalizations or known probability of selection. This contrasts with probability samples, where random selection methods like simple random or stratified random sampling provide each unit with a known chance of inclusion and support population-level inferences with sampling error estimates. So, the method described is purposive sampling, chosen for its ability to yield rich, targeted insights relevant to the research question.

Selecting participants based on the researcher's judgment for a specific purpose is purposive sampling. This non-probability approach focuses on choosing cases that are especially informative or representative of a phenomenon you want to study, such as individuals with particular experiences, expertise, or characteristics. The aim is depth and relevance rather than generalizability to the entire population.

Because the researcher purposefully selects cases, not every member of the population has an equal chance of inclusion, and you can’t rely on statistical generalizations or known probability of selection. This contrasts with probability samples, where random selection methods like simple random or stratified random sampling provide each unit with a known chance of inclusion and support population-level inferences with sampling error estimates.

So, the method described is purposive sampling, chosen for its ability to yield rich, targeted insights relevant to the research question.