Probability Sampling Design Explained

Probability sampling designs give every member of the population a known, non-zero chance of being selected. This ensures that the sample is representative of the population.

Cluster Sampling as Probability Sampling

Cluster sampling is a probability sampling method. In this technique, the population is divided into groups or 'clusters' (often naturally occurring, like geographical areas). Then, a random sample of clusters is selected, and all individuals within the selected clusters are included in the sample.

Why Other Options Are Not Probability Sampling

• Quota sampling: This is a non-probability method where samples are selected based on pre-set quotas for certain characteristics, without random selection.
• Snowball sampling: This non-probability technique relies on initial participants referring others who meet the criteria, useful for hard-to-reach populations.
• Purposive sampling: This non-probability method involves selecting participants based on the researcher's judgment and the purpose of the study.

Conclusion

Among the given options, only cluster sampling is a recognized probability sampling design because it involves random selection at the cluster level.