Question

Which one of the following sampling strategies does NOT implement simple random sampling at any point during its implementation?

a) Simple Random Sampling
b) Cluster Sampling
c) Stratified Sampling
d) All of these strategies implement simple random sampling at some stage.

Answer 1

Cluster Sampling is the sampling strategy that does not use simple random sampling at any point, as it selects all individuals within a few randomly chosen clusters.

Step-by-step explanation:

The sampling strategy from the options provided that does NOT implement simple random sampling at any point during its implementation is b) Cluster Sampling. In cluster sampling, the population is divided into clusters, usually based on geography or some other logical division, and then a few clusters are selected at random. After selecting the clusters, all individuals within the chosen clusters are sampled.

In contrast, simple random sampling involves randomly choosing individuals from the entire population so that each individual has an equal chance of being selected. Stratified sampling divides the population into strata, then randomly selects individuals from each stratum. So, both simple random sampling and stratified sampling involve some form of random selection at the individual level, unlike cluster sampling.