Quota Sampling

Quota sampling in statistics refers to a non-probability sampling technique that involves researchers creating a convenience sample with individuals representing a population. Individuals or organizations can use this method to gain insights regarding a specific subgroup’s characteristics. Moreover, they can utilize this technique to investigate the relationships between multiple subgroups.

This technique allows one to control who or what makes the sample. The design may involve equal numbers of various types of respondents, mimic the population of interest’s true composition, and over-sample a specific kind of respondent, even if the population proportions differ. This technique is of two types — uncontrolled and controlled.

• Quota sampling refers to a sampling method utilized by organizations and individuals to prepare a convenience sample with only the individuals that represent their target audience.
• It allows people to focus on a particular trait within a certain subgroup. It also helps compare associations between different subgroups. 
• The quota sampling technique has two categories — uncontrolled and controlled.  
• Both quota and purposive sampling processes involve using non-random random sampling techniques, while the stratified sampling technique involves utilizing random sampling. 
• A key benefit of quota sampling is that it requires a low budget.

Quota sampling in statistics refers to a non-probability sampling method relying on a proportion or a predetermined number of units’ non-random selection. It is a popular technique used by people to accumulate data in research studies and surveys. In this process, one creates a sample of people who represent the target market.

Individuals or organizations choose the people per categories or quotas representing their audiences’ particular characteristics. Additionally, one must ensure that the composition of the final sample fulfills the requirements of the study’s quota.

Note that with every additional quota, it takes longer for people to get suitable respondents. Moreover, this adds both time and cost to the process of quota sampling. A sample acquired using this technique consists of proportions of observations similar to the entire population with a few known characteristics or traits.

Let us look at a few features of this sampling method to understand how it works:

• The quality of the quota samples varies.
• The sample is a whole population’s representation.
• Researchers always divide the population into different subgroups.
• A researcher uses his technique to spot traits of a particular group of individuals.
• It aims to get respondents’ best representation in the ultimate or final sample.

As noted above, this non-probability sampling technique has two types. Let us understand them.

• Uncontrolled Sampling: In this process, the sampling technique does not impose limitations on statisticians or researchers’ sample choice. This means a researcher is able to choose a sample of their interest.
• Controlled Sampling:  In this case, there are restrictions imposed on the researchers' or statisticians’ sample choice. As a result, a researcher can only choose a limited sample.

Let us look at the steps one needs can follow to use this sampling technique.

1. Divide the audience into categories or segments on the basis of relevant quotes, such as income, job role, and gender.
2. Identify all proportions of the segments or categories in the audience. Note that identical proportions will apply to the sample.
3. Choose participants from every category while following all proportions identified in the previous step.
4. Lastly, double-check to make sure that the sample is a representation of the target audience. Not that getting a perfect match is not the point, as that is impossible. Rather, one must get a sample that includes all the vital characteristics of every sample.

Let us look at a few quota sampling examples to understand the concept better.

Example #1

Suppose a liquor company, Company ABC, carrying out operations in New York City, wants to determine what age group prefers which alcohol brand offered by it. The organization applied the quota sampling technique using age groups of 21-28, 29-35, 36-45, 45-60, and more than 60. By utilizing this technique, the company was able to get an idea of the drinking trends among the city’s population.

Example #2

Suppose a tobacco company, XYZ, wants to know about the types of juices preferred by the people of a city. Specifically, it wants to know about the differences in the choice of flavor among people aged 10-30, 31-50, and above 50. Suppose the total number of people aged at least 10 is 100,000. The company has to divide the total number of individuals into different categories with regard to the above three age ranges. Suppose it finds that there are 1,000 people aged 10 (1%), 80,000 people aged 31-50 years (80%), and 19,000 people aged above 50 (19%). Thus, XYZ can start accumulating samples from these people based on their proportion.

Let us look at the benefits and limitations of this sampling method.

Advantages

• The sampling process is straightforward and quick because it involves a quota for creating the sample. Hence, this technique saves time.
• In this technique, there is no scope for over-representation because the sampling method allows researchers to study all individuals in the whole population utilizing particular quotas.
• The budget requirement for this method is minimalistic.
• Another key benefit of quota sampling is that it offers research convenience.

Disadvantages

• Since the quota sampling technique does not involve utilizing random selection. Hence, it can result in research biases, for example, selection bias.
• There’s a high chance of inaccuracy as researchers only consider specific characteristics when stratifying a sample into different subgroups.
• Dividing the whole population into different mutually exclusive groups is always possible as people may be a part of multiple groups.

The concepts of quota, stratified, and purposive sampling can be confusing for people, especially if they do not clearly know how their meanings and purposes differ. So, to steer clear of confusion, let us look at the critical differences between these sampling techniques.

This article has been a guide to what is Quota Sampling. We explain its examples, types, advantages, steps, and comparison with stratified & purposive sampling. You may also find some useful articles here -

• Sampling Theory
• Data Sampling
• Sampling Error