Answer:
Convenience Sampling
Step-by-step explanation:
Lets talk about each of the sampling methods one by one:
Cluster Sampling: It is a type of sampling method in which a researcher divides the population into separate groups, which they call it 'clusters'. Then, a random sample of clusters is selected from the population. The researcher conducts his analysis on data from the sampled clusters.
Stratified Sampling: It is a type of sampling method in which a researcher divides the population into separate groups, called strata. Then, a probability sample (often a simple random sample) is taken out from each group.
Convenience Sampling: It is one of the main types of "non-probability sampling methods". A convenience sample is made up of population who are easy to reach out.
Random Sampling: It is a part of the sampling technique in which each sample has an equal probability of being picked. When the sample is chosen randomly it is meant to be an unbiased representation of the total population.
Now among all these methods, Convenience sampling method is the weakest because it lags the representation of the entire population, also the sample is not chosen randomly. And hence no generalization can be made about the population under study.
