In practice, systematic sampling is used on account of its simplicity and convenience. It's easy to explain to the people doing the actual work.
It can be justified theoretically wherever the population from which units are to be sampled systematically are randomly distributed.
It can be used for sampling households, sampling callers on a telephone line, sampling plants along a transect in (say) a field, sampling people passing through customs, and so on.
Chat with our AI personalities
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
You can't conduct startified sampling if there are no difinative groups, thus systematic sampling is more efficient if your data has no groups.
Disadvantages of systematic sampling: © The process of selection can interact with a hidden periodic trait within the population. If the sampling technique coincides with the periodicity of the trait, the sampling technique will no longer be random and representativeness of the sample is compromised.
random sampling ,systematic sampling , self-selected , and there is one more i don't know
Nothing! there the same