Which sampling method selects sample members to study because they possess attributes important to understanding the research topic?

Which sampling method selects sample members to study because they possess attributes important to understanding the research topic?

• A. Purposive Sampling
• B. Snowball Sampling
• C. Quota Sampling
• D. Cluster Samples

Answer: (A)

Purposive sampling focuses on selecting participants who have specific characteristics that are directly relevant to the topic being studied. By targeting individuals with those attributes, you maximize the likelihood that the data will illuminate the research question and yield meaningful insights. This approach is common in qualitative research where depth and relevance trump broad representativeness. Snowball sampling, by contrast, relies on initial participants to nominate others, which helps access hard-to-reach groups but doesn’t prioritize the attributes needed to understand the topic. Quota sampling aims to fill predefined subgroups to resemble a population, focusing on representation rather than selecting for particular topic-relevant attributes. Cluster sampling selects whole groups for practicality and representativeness at the group level, not on individual attributes tied to the topic. So, selecting sample members specifically because they possess the attributes important to understanding the topic is Purposive sampling.

Purposive sampling focuses on selecting participants who have specific characteristics that are directly relevant to the topic being studied. By targeting individuals with those attributes, you maximize the likelihood that the data will illuminate the research question and yield meaningful insights. This approach is common in qualitative research where depth and relevance trump broad representativeness.

Snowball sampling, by contrast, relies on initial participants to nominate others, which helps access hard-to-reach groups but doesn’t prioritize the attributes needed to understand the topic. Quota sampling aims to fill predefined subgroups to resemble a population, focusing on representation rather than selecting for particular topic-relevant attributes. Cluster sampling selects whole groups for practicality and representativeness at the group level, not on individual attributes tied to the topic.

So, selecting sample members specifically because they possess the attributes important to understanding the topic is Purposive sampling.