Explain the similarities and differences between cluster sampling and multi-stage sampling.

Cluster sampling involves having each member of the selected "cluster" surveyed, while in multi-stage sampling, only a select few of members from each cluster is surveyed. On the contrary, they are similar in the sense that they are both divided into heterogeneous groups called clusters.

Cluster Sample: If certain groups are likely to be representative of the entire population, you can use a random selection of such groups as a cluster sample. For example, a fast-food chain could save time and money by surveying all its employees at randomly selected locations instead of surveying randomly selected employees throughout the chain.

Multi-Stage Sample: A multi-stage sample uses several levels of random sampling. If, for example, your population consisted of all Ontario households, you could first randomly sample from all cities and townships in Ontario, then randomly sample from all subdivisions or blocks within the selected cities and townships, and finally randomly sample from all houses within the selected subdivisions or blocks.