Quota Sampling

The sample and population are the two most important terms used in Statistics. A population is the whole area of study, whereas a sample is the part of the population on which the calculations are performed, and the result is interpreted. The process of choosing and selecting an adequate sample for research is known as sampling. The sampling technique involves the selection of a set of observations from a statistical population, characterizing the whole population. Sampling is widely applicable in Medical Research and Business to collect information about a given population. There are different sampling methods. In this article, we are going to discuss one of the sampling techniques called “Quota Sampling” in detail with its types and steps with complete explanation.

Table of Contents:

• Definition
• Types
• Steps
• Uses
• Example
• FAQs

Quota Sampling Definition

Quota sampling is an important sampling method that involves a non-probability sampling technique in which sampling is not based upon the probability of appearance. In such a process, the researcher decides the selection of sampling based on some quota. In quota sampling, the researcher makes sure that the final sample must meet his quota criteria.

“The sample obtained from a quota sampling method contains similar proportions of observations as the whole population with some known traits or characteristics. In quota sampling, the researcher selects from his/her judgement or some fixed quota. In other words, the sample observations are to be chosen based on some pre-specified virtues. Then the total sample contains the same distribution of characteristics that were assumed to be found in the population of concern”.

Types of Quota Sampling

The quota sampling is classified into two different types, such as:

• Controlled Quota Sampling
• Uncontrolled Quota Sampling

Controlled Quota Sampling:

If the sampling imposes restrictions on the researcher’s/Statisticians choice of sample, then it is known as controlled quota sampling. In this method, the researcher can be able to select the limited samples.

Uncontrolled Quota Sampling:

If the sampling does not impose any restrictions on the researcher’s/Statisticians choice of sample, then it is known as uncontrolled quota sampling. In this process, the researcher can select the samples of their interest.

Quota Sampling Process

The steps for the process of quota sampling are listed below:

Step 1: Firstly, the population should be divided into mutually exclusive subgroups

Step 2: Next is to determine the proportions of the subgroups made in the previous step, since the same proportion would be used during the sampling process

Step 3: Now, the researcher has to choose individual observations or items from the subgroups. Also, the proportions found previously are to be taken into consideration

Step 4: The last and final step is to ensure that the obtained sample should be representative of the whole population and allow the researcher to study characteristics and traits.

Uses of Quota Sampling

Some of the essential uses of quota sampling are as follows:

• In quota sampling, the judgment of sampling is done on the basis of convenience or a fixed quota. It is used when the decision of the researcher is final for choosing the samples
• The quota sampling is used because it allows the researchers to select a subgroup as a sample that is of great interest to study
• This method is used when the researcher wants to determine the relationship between the subgroups
• The quota sampling method should be selected when there is a limited time

Quota Sampling Example

An example is given below to understand the concept of quota sampling:

Let us assume that we need to know about the career goals of university students. More particularly, the differences in the career goals among fresher, juniors and seniors are to be examined. Suppose the concerned university contains 10,000 students and can be taken as our population.

Now, we have to divide our population of 10,000 students into categories such as freshers, juniors and seniors. Suppose we find that there are 3000 freshers (30%), 2500 junior students (25%) and 2000 senior students (20%). Our sample must have these proportions. It means that if we sample 1000 students, then we must consider 300 freshers, 250 juniors and 200 seniors. Lastly, we may start collecting samples from these students based on our proportion.

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