Which sampling technique selects all individuals from randomly chosen clusters?

Which sampling technique selects all individuals from randomly chosen clusters?

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

Answer: (A)

The idea here is how to sample by using whole groups. In cluster sampling, you divide the population into natural groups or clusters (like schools, neighborhoods, or clinics). You then randomly select some of these clusters, and include every individual within the chosen clusters in your study. This approach is efficient when the population is spread out and listing every individual would be costly. This matches the description of selecting all individuals from randomly chosen clusters. Snowball sampling relies on participants referring others and isn’t random. Quota sampling fills predefined subgroups but still isn’t random within those groups. Purposive sampling selects specific cases deliberately, also not random.

The idea here is how to sample by using whole groups. In cluster sampling, you divide the population into natural groups or clusters (like schools, neighborhoods, or clinics). You then randomly select some of these clusters, and include every individual within the chosen clusters in your study. This approach is efficient when the population is spread out and listing every individual would be costly.

This matches the description of selecting all individuals from randomly chosen clusters.

Snowball sampling relies on participants referring others and isn’t random. Quota sampling fills predefined subgroups but still isn’t random within those groups. Purposive sampling selects specific cases deliberately, also not random.