Quota sampling is a type of non-probability sampling in statistics and research. It is somewhat similar to stratified sampling except that it is a non-random sampling method. Its use is more common when there is no obvious sampling frame available or the researcher has a low budget and less time to undertake the research.
The method for sample selection in quota sampling is same as in stratified random sampling. But, the major difference lies in that the researcher selects samples from each subgroup based on judgement. So, in essence it is also a type of judgmental sampling because the researcher uses his judgement or knowledge as a base to select sample. But, of course, it is also different because there are subgroups and the samples are selected from each subgroups. The researcher follows the following steps to draw sample in this method.
- First, the researcher identifies possible segments of the population under study. And the population is divided into subgroups, each subgroup is mutually exclusive.
- Next, the researcher decides on the number of units from each subgroup. The proportion of sampling units from each subgroup may or may not be same.
- The researcher then draws samples from each subgroup based on judgment, convenience, or availability. Because it is a non-random method the researcher selects any sampling unit that fits in subgroup criteria. This often makes it very subjective and less reliable.
Problems with quota sampling
- It is hard to believe that a sample that the researcher selects based on his judgment is representative of the total population. But, then in qualitative research it is not always possible to select a sample randomly.
- Some researcher use quota sampling as an alternative to stratified random sampling because it saves time and is low budget. If a researcher is using quota sampling because of resources constraint he should follow accurate methods to make it reliable.
- Due to the non-random nature of this sampling method one cannot find the sampling error in this method.
Dealing with the issues of non-randomness
Though quota sampling presents a problem of unreliability we can handle it in a manner that makes it more worthy and reliable in any qualitative research.
- The researcher has a responsibility to put back biases, prejudices, or any type of clumsiness. You cannot select a sample on the basis of ease of selection, or with carelessness. Every researcher need to have aptness and should not compromise unless it is not possible otherwise.
- Of course, this also poses the question how to prove that the researcher took all precautions and did not bring any biases in the sample selection. The researcher needs to provide all the steps and actions that he took to avoid subjectivity in the sample selection in quota sampling.
- Also, the researcher should provide basis for the preference of quota sampling and not any other more reliable method. The researcher might select quota sampling because the sampling frame is not available.
- Another important consideration is that the researcher should choose a sample size that is representable and most appropriate for the total population.