Quota Sampling

To understand Quota Sampling, you need to first understand the meaning of sampling. Used primarily in statistics, sampling refers to selecting a section or subset in a population and then analyzing it based on several factors. Sampling is generally done to be time and cost-efficient. It is because of sampling that we get to identify similarities and preferences in a population; based upon their attire, age-groups, likes, etc. Useful in a variety of scenarios, like in healthcare research, or understanding the target groups in a country's population for brands, sampling can be done in several ways, including the quota sampling method.

Quota Sampling Definition

The meaning of Quota Sampling refers to the event when we gather samples within a group based on their specific characteristics or behaviors, depending upon their population size. The quota sampling process can be defined as a non-probability sampling method that is useful in making a sample for researchers, based on the general features in a given population. 

Here's When to Use Quota Sampling: 

The above chart depicts the population of women from different age groups, scattered across the community. For the fashion designer to understand the behavior and traits of women from specific age groups, gathering data without segregating the age groups would prove meaningless for gaining insights. 

Different Types of Quota Sampling

Overall, quota sampling can be divided into two types, namely: Controlled Quota Sampling and Uncontrolled Quota Sampling.

Controlled Quota Sampling

Such situations refer to the cases when the researcher or survey conductor is limited to the sample choices. For example, if a school bag maker wants to survey students' preferences for school bags, in general. Here the research would be limited to the children in their school-going age. 

Uncontrolled Quota Sampling

Any situation where the researcher or analyst doesn't have any constraints or limitations for the sampling process is called Uncontrolled Quota Sampling. An example of an uncontrolled quota sampling can be that of a study conducted by medical workers to understand the overall public health and well-being in a nation-state at a regular period of interval. Here, the study would comprise samples from all age-groups, place of residence, gender, and more in the general population. 

Quota Sampling Process

In general, probability sampling techniques can comprise several steps to form meaningful samples. Since quota sampling is a non-probability sampling technique, various steps go into selecting samples carefully. They are:

Step I: Data Assessing and Division into Subgroups 

Also known as the stratified sampling, here the researcher goes through the population and divides it into mutually exhaustive subgroups based on the traits of: 

  • Age group

  • Height

  • Gender

  • Educational Qualification

  • Area of Belonging

Step II: Calibrating the Weightage of SubGroups 

After the researcher has decided upon the subgroups, he/she needs to evaluate the proportion of the subsets compared to that of the population. This process helps in determining the number of samples to be taken from each group for further analysis. 

The General Formula for the Proportion Followed Will Be

The number of samples taken from a group = 

(Number of items present in the group) x \[\frac{Total\;Samples \;to \;be \;Taken}{Total\; Items\; Present\; in\; the\; Population}\]

Step III: Appropriate Sample Selection 

Here the researcher needs to select the overall size of the samples, in alignment with the correct proportions derived from the previous step. 

Here's an example of the sample size for a perfume manufacturer conducting a study to identify buying trends in men and women:

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The above chart shows the relative proportions of various age groups in the population and the number of samples needed from respective age groups. 

Step IV: Survey Underway according to Set Quotas 

As a researcher, you need to stick to the already-set quotas for actionable and relevant results. 

Uses of Quota Sampling in Different Fields

  • Quota sampling helps in achieving the best data representation model in terms of its fixed quotas or samples. 

  • The quotas are the closest to the population trends and interests in terms of reality.

  • Quota sampling helps researchers to track any underlying relationships between different subsets and identify various trends in specific people. 

  • It is with the help of quota sampling that researchers get surveys done in a short period and reduced involved costs.

Quota Sampling Example

Let us consider a perfume maker who wants to understand the buying preferences of people for his perfume. (see Quota sampling process, step III)

As the researcher needs to go deep into the shopping choices of buyers - men and women, he needs to subset the population into respective samples. Therefore, once he completes the necessary research process, he finds that out of the total footfalls/buyers of his perfume was 10,000. 

In them, there were 4000 men (40%) and 6000 women (60%). The sample that we select needs to reflect the same percentages to stay relevant for the study. Therefore, every time the researcher considers 1000 of his buyers, he needs to take account of 400 men and 600 women, respectively. 

FAQ (Frequently Asked Questions)

1. When to Use Quota Sampling in a Study?

Quota sampling is deemed fit to use for research in a particular scenario where one needs to monitor any relationships between other samples in the study. 


It is also useful for data analysis that doesn't require pinpoint accuracy and can yield valuable results even on a close-to-reality data model. For study projects with time and budget constraints, quota sampling is the best way to achieve quality results. From medical professionals to manufacturing business owners, quota sampling is used across many domains. Such non-probability sampling methods also have the best-use cases for theoretical contribution and explanation purposes.

2. Is Quota Sampling Purposive?

Any method that comes from a specific purpose and has more than one set subgroup is called purposive sampling. There can be many other sampling methods that can be deemed as purposive sampling, including that of quota sampling. In such cases, the researchers need to get to the predefined samples quicker and gather opinions or preferences of the subsets, based on the proportions of the entire population.


For purposive sampling, the intention can be for identifying diversity or similarity, reaching specific target groups who are otherwise left out in the consideration. Other methods, like snowball sampling, are also known as purposive sampling.