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Quota sampling is a type of judgment non-probability sampling. In a quota sample, the population is divided into groups according to specified characteristics such as income group, age, political affiliation, etc. Within the quota, the selection of the sample items depends on the personal judgment of the investigator.

Quota Sampling – Definition

One can think of quota sampling as a particular kind of stratified sampling. In this procedure, the investigator is given advance notice of how many sample units from the stratum he has been assigned to inspect or count. According to the terminology of stratified sampling, each investigator is given a definite number of units from the stratum that has been assigned to him to examine. Sample quotas may be set according to a specific attribute, such as economic level, sex, occupation, political or religious affiliations, etc.  The decision as to which specific units or people to look into is left up to the investigators.  Simply put, they are given quotas and told to interview a set number of units from each stratum.

The researcher does not choose the sample units at random. He typically uses his discretion and judgment in selecting the sample and works to obtain the relevant information as soon as possible. Additionally, the investigator chooses some new units on his own to meet his quota in the event that some of the sample units he had chosen did not respond (due to factors like the respondent’s unavailability despite repeated calls from the investigator or the informant’s inability or refusal to provide the necessary information).

Examples of Quota Sampling:

Example 1:

In a survey of listeners of a particular radio show, the interviewers may be told to interview 500 people within a certain area. Or else, they may be told to ensure that at least 20% of the people interviewed belong to the older demographic (say, more than 60 years of age). Within these quotas, the interviewer is free to select the people to be interviewed.

Example 2:

In a research study of the lifestyle habits of Americans, it might be useful to include people from a wide variety of income levels and ages. The investigator may decide to interview ten men and ten women such that two of them earn more than $2 million annually, five earn between$1 and $2 million annually, and thirteen earn less than$1 million annually. Additionally, some of them should be between the ages of 25 and 35, others between the ages of 36 and 45, and the remainder should be older than 45. This means that these “controls” have some influence on the results of the study.

1. Since it combines stratified and judgment sampling, quota sampling enjoys both of their advantages. By avoiding the significant expenses associated with using any probabilistic sampling method, it tries to make the best use of stratification. As the sampled units can be chosen to be near together, there is a significant time and financial savings.
2. Quota sampling is likely to produce results that are highly reliable if it is skillfully carried out by investigators who are knowledgeable about the restrictions of judgment sampling and if appropriate controls or checks are established on the investigators.

The main disadvantage of quota sampling is that there are many ways for bias to creep in, which will invalidate the results of the survey.

1. It could be biased as a result of the investigator’s personal convictions and prejudices when choosing the units or checking them.
2. It can include bias brought on by the replacement of sampled units where there is no response. Quota sampling is mostly based on participant availability or volunteers. If a person simply refuses to respond to the interviewer, the interviewer might then select someone else based on his own personal preference which increases the risk of bias.
3. It is not based on random sampling, hence it is impossible to quantify the sampling error.

Quota sampling vs Stratified sampling:

Quota sampling and stratified random sampling similar in the sense that in both methods the population is divided into parts (called quotas/strata) and the sample is chosen from these parts. The difference between stratified sampling and quota sampling is that in stratified random sampling, the selection within the group/strata is done at random whereas in quota sampling the selection within the quotas is not random but at the discretion of the researcher. Each element in the population DOES NOT have an equal chance of being selected in quota sampling.

Convenience sampling vs Quota sampling.

The difference between convenience sampling and quota sampling is that in convenience sampling the sampling units are chosen at the convenience of the researcher. The researcher includes those sample points that he prefers based on personal convenience. There are no quotas that the researcher is required to follow. On the other hand, in quota sampling, the researcher must fulfill the quotas when selecting the sample. He cannot choose any sample point as per his preference and disregard the quota. The only similarity between both methods is that in both methods the sample is selected in a non-random fashion.

Uses of Quota Sampling:

Quota sampling is most commonly used in public opinion studies, marketing research, and political surveys. It can provide satisfactory results if the interviewers are carefully trained in order to eliminate all sources of personal bias. Quota sampling is advisable for public opinion surveys when the interviewers are well trained and have the background knowledge required for the study. Quota sampling is typically used in situations when it is extremely difficult to determine the strata in advance.

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