QUOTA SAMPLING

 What is quota sampling?

Quota sampling is defined as a non-probability sampling method in which researchers create a sample involving individuals that represent a population. Researchers choose these individuals according to specific traits or qualities.



Types of quota sampling:



Quota sampling can be of two kinds – controlled quota sampling and uncontrolled quota sampling. Here’s what they mean:  

controlled quota sampling: 

Controlled quota sampling imposes restrictions on the researcher’s choice of samples. Here, the researcher is limited to the selection of samples.

Uncontrolled quota sampling

Uncontrolled quota sampling does not impose any restrictions on the researcher’s choice of samples. Here, the researcher chooses sample members at will.  

Characteristics of quota sampling: 

Here are the top ten characteristics of quota sampling

Aims to get the best representation of respondents in the final sample.

Quotas replicate the population of interest in a real sense.

The estimates produced are more representative.

The quality of quota samples vary.

Saves research data collection time as the sample represents the population.

Saves research costs if the quotas accurately represent the population.

It monitors the number of types of individuals who take the survey.

The researcher always divides the population into subgroups.

The sample represents the entire population.

Researchers use the sampling method to identify the traits of a specific group of people.

Advantages of quota sampling

Here are the top four advantages of quota sampling


Saves time: Because of the involvement of a quota for sample creation, this sampling process is quick and straightforward.

Research convenience: By using quota sampling and appropriate research questions, interpreting information and responses to the survey is a much convenient process for a researcher.

Accurate representation of the population of interest: Researchers effectively represent a population using this sampling technique. There is no room for over-representation as this sampling technique helps researchers to study the population using specific quotas.

Saves money: The budget required for executing this sampling method is minimalistic(Dan,2020).

How to get quota sampling right

Unlike random sampling or stratified sampling, quota sampling has no formal rules or proportions. Follow the steps below to get quota sampling right.


1. Divide the sample population into subgroups


These should be mutually exclusive. For example, you might divide a certain student population by their professional degree courses, such as engineering, arts, humanities, and medicine.

2. Figure out the weightages of subgroups

The weightage is how much of your sample a given subgroup will be. For example, you can assign a weightage of 25% for engineering students, 30% for humanities students, 15% for arts students, and 30% for students specializing in medicine.

3. Select an appropriate sample size

The quota size should be representative of the collective subgroup population. For example, you can select a total sample of 500 students from a population of 50,000 students.

4. Survey while adhering to the subgroup population proportions


Choose survey respondents based on the weightages allotted in Step 2. For our example, survey engineering students until you reach the specified weightage — 25% of the 500-student sample, which is 125 students. Continue with this process until all the quotas are filled and 500 students have been surveyed

quota sampling, sampling( Amrutha, 2016).

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References 

Dan,F. (2020). Quota sampling: Definition, types, examples, steps, and more. https://www.questionpro.com/blog/quota-sampling/amp/

Amrutha,A. (2016).Quota Sampling: When To Use It and How To Do It Correctly.https://humansofdata.atlan.com/2016/04/quota-sampling-when-to-use-how-to-do-correctly

Safiza,M. (2017) Quota sampling.https://youtu.be/K8lcSHlB64w

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