Systematic sampling is an often-used sampling strategy and cost effective. Again, you must have a population sampling frame list that is in random order and non-overlapping. Determine both the size of the population and the size of the sample you want to work with. Then, divide the sample size (n) into the population (N) size to get your key number, symbolized as “k”. That is your systematic sample.
Cluster sampling is exactly what its title implies. You randomly select clusters or groups in a population instead of individuals. That is your cluster sample.
Quota sampling is used if a stratum is small in the population but important to the research questions being presented. So we may over sample, or establish a quota, so that we get the subjects needed to address our research. That is your quota sample.
Stratified sampling is used when the population is heterogeneous and it is important to represent the different strata or sub-populations. There is a proportional representation of strata in the sample - proportional to the population strata. We divide the entire population into strata (groups) to obtain groups of people that are more or less equal in some respect. Then, select a random sample from each stratum. That is your stratified sample.
Convenience samples, exactly what the name suggests, are oftentimes what we have to use because of reality. We cannot draw a sample, but we have a group that is accessible, is representative of our target population and just available to us. Instead of becoming purists and throwing out the chance for collecting data for decisions, use what you have with the honest acknowledgement that there are limitations. That is your convenience sample.