Statistical Methods

Step 1: Understanding non-random sampling.
Non-random sampling involves selecting a sample in a way that does not give all members of the population an equal chance of being selected.

Step 2: Analysis of options.
- (A) Convenience sampling: This is a non-random sampling method where individuals are selected based on ease of access.
- (B) Cluster sampling: This is a random sampling method where the population is divided into clusters, and some clusters are randomly selected.
- (C) Quota sampling: This is a non-random sampling method where the researcher selects a sample to meet specific quotas.
- (D) Snowball sampling: This is a non-random sampling method where existing subjects recruit new subjects.

Step 3: Conclusion.
Cluster sampling is a random sampling method, so the correct answer is (B).

Sampling techniques can be classified into random and non-random sampling. Random sampling methods give each individual in the population an equal chance of being selected, while non-random sampling methods do not. - (A) Convenience sampling: This is a non-random sampling method where samples are selected based on ease of access or convenience, making it a non-random sampling technique.
- (B) Cluster sampling: This is a random sampling technique where the population is divided into clusters, and some clusters are randomly selected to participate in the study. Therefore, it is not a non-random sampling method.
- (C) Quota sampling: This is a non-random sampling technique where the researcher selects a sample that meets certain quotas or characteristics, making it non-random.
- (D) Snowball sampling: This is a non-random sampling technique where participants are asked to refer other participants, and the sample grows in this way, which makes it a non-random technique.
The correct answer is (B), as cluster sampling is a type of random sampling. Final Answer: (B) Cluster sampling.