is a method for selecting survey participants. In quota sampling, a population is first segmented into mutually exclusive
sub-groups, just as in stratified sampling
. Then judgment is used to select the subjects or units from each segment based on a specified proportion. For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. This means that individuals can put a demand on who they want to sample (targeting)
This second step makes the technique non-probability sampling. In quota sampling, the selection of the sample is non-random sample
and can be unreliable
. For example, interviewers might be tempted to interview those people in the street who look most helpful, or may choose to use accidental sampling
to question those closest to them, for time-keeping sake. The problem is that these samples may be biased
because not everyone gets a chance of selection. This non-random element is a source of uncertainty about the nature of the actual sample and quota versus probability has been a matter of controversy for many years.
Quota sampling is useful when time is limited, a sampling frame
is not available, the research budget is very tight or when detailed accuracy is not important. Subsets are chosen and then either convenience or judgment sampling is used to choose people from each subset. The researcher decides how many of each category is selected.
Quota sampling is the non probability version... Read More