Remember: we talk about nonrandom sampling when we don’t have access to a full list of the individuals who form the population (a sampling frame) and thus don’t know the probability that a given individual will be selected for the sample.
The main consequence of this lack of information is that we can’t generalize the results with statistical precision.
Availability sampling is used quite frequently. It involves selecting a sample from the population because it is accessible. That is to say, individuals are selected for the research not because they meet some statistical criterion, but because they are readily available. This convenience usually translates to easy operation and low sampling costs. The trade-off, of course, is that it is impossible to use the results to make general assertions about the population with any sort of statistical rigor.
Suppose that we want to know Chilean college students’ thoughts on politics. To get a random sample, we would need a list of all the students in all of the universities in Chile so that we could randomly select a group of individuals and interview them. To get an availability sample, on the other hand, we might meander over to the three universities closest to where we live and survey however many individuals agree to participate when we catch them between classes.