Quota Sampling Polynomial regression

All you need to know about Quota Sampling

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Surveys are the most common method to gather insights from the target population. Whether it is the fans of Disney movies or customers of a beauty brand, you cannot survey all of them at the same time. So, the researchers found ways to create samples from the target population to gather representative data – i.e. the data that represents the entire target population. 

One such popular method is quota sampling. So before you go about creating samples of your target audience you need to understand what is quota sampling, its benefits, weakness, and how it works. And, this blog will help you learn all that. 

We will start with the definition of quota sampling and how researchers create quota samples to conduct surveys.

What is Quota Sampling?

By definition of quota sampling, it is a type of non-probability sampling method. This means that elements from the population are chosen on a non-random basis and all members of the population do not have an equal chance of being selected to be a part of the sample group.

In this method of sampling, researchers typically use market research software to create two stages to acquire their quota sample. 

  • First, they list relevant control characteristics and their distribution in the target population. 

This is done to ensure that the composition of the selected sample group is representative of the composition of the target population (in regard to the listed control characteristics). 

These “control characteristics” can be variables such as age, race, and sex. Researchers create these groups based on their own judgment.

  • The second stage is to select elements for the sample group based on the convenience and/or judgment of the researcher. 

This is what differentiates this type of sampling from stratified sampling, as stratified sampling uses SRS (simple random sampling) or other probability sampling methods to choose elements for the sample group once the strata are divided. 

To define quota sampling precisely, it is a two-stage non-probability sampling method that assigns quotas to the population in order to ensure that when elements of the population are selected, the sample group is representative of the population’s characteristics. After quotas are assigned, researchers choose elements from the subgroups using convenience or judgment. 

Now that we have established the quota sampling definition, we will move on to its two types.

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What are the types of quota sampling?

With the definition of quota sampling out of the way, we can now focus on the two types. For market research tools, it can be divided into two broad categories. 

  1. Controlled sampling: This type imposes certain limitations on the researcher’s choice of samples.
  2. Uncontrolled sampling: It does not impose any limitations or restrictions on the researcher’s choice of samples.

The absence of random selection is what separates this sampling method from the rest. This is an ideal sampling method when the goal is to gather insights about certain characteristics of a particular sample group. 

We will now look at the three simple steps you need to follow to create a quota sample.

Quota Sampling Polynomial regression

How to perform quota sampling?

To create a quota sample you don’t have to follow any specific hard-and-fast rules. However, as we mentioned in the definition of quota sampling, there are some guidelines that you should keep in mind when creating quota samples. 

Here are four easy steps you need to perform: 

Step-1: Divide the population into subgroups according to relevant control characteristics. The subgroups should be mutually exclusive and collectively exhaustive so as to not have an overlap of elements in subgroups.

Step-2: Define the proportions of the subgroups in order to decide how many elements will be chosen from each subgroup (quotas).

Step-3: Select an appropriate sample size and then select elements from subgroups keeping in mind how many elements can be selected from each subgroup (the quotas).

Step-4: Survey your audiences until you have fulfilled the sample size. Your survey is complete after you have reached the determined quota.

To better understand how to perform this sampling method, let’s look at the example in the next section.

Example of Quota Sampling

Let’s assume that a researcher wants to study the buying habits of the people in New York depending on their gender and employment status. In this example, gender and employment status will be the “relevant control characteristics”, using which the quotas will be decided.

Let’s consider the following factors for the quota sampling example. 

  • Employment Status
    • 10% of New York’s workforce is unemployed
    • 90% of New York’s workforce is employed
  • Gender 
    • 40% of New York’s population identifies as male.
    • 60% of New York’s population identifies as female.

Researchers will then use this information to reflect similar proportions of male/female and employed/unemployed in their sample group. 

Let’s say a sample size of 100 people is decided upon. Researchers will use market research tools that have quotas to decide how many males and females are chosen in regard to their employment status. 

Therefore, they may choose to include 60 females and 40 males, 10 of which are unemployed. These elements will be chosen by the researcher on the basis of convenience or judgment.

The next question that comes up often is when can you use this sampling method.

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When can quota sampling be used?

With this type of sampling, you can select subgroups, which makes it ideal for research. You can gather desired results from your surveys. 

Here are five scenarios when you can use this type of sampling method to study the population. 

  1. You can use it to compare two subgroups and determine the distinguishing features among the shared characteristics. For example, the use of social media of boomers vs millennials. 
  2. When researchers have a limited time frame, they can use quota sampling as it is a relatively quick method of sampling. This is because it uses convenience or judgment sampling to select elements once quotas are assigned.
  3. This method of sampling is also relatively cheaper than other methods, hence, it is also used when researchers have a limited budget.
  4. When the researcher is interested in studying certain subgroups of the population, this is the next best option after stratified sampling. It aims to select sample groups that are representative of the population but is also not as expensive and time-consuming as stratified sampling. 
  5. You can use this method when you have predetermined criteria to survey. It is very convenient because you can filter the characteristics to create a quota sample.

What are the advantages of quota sampling?

It is a popular choice among researchers for many reasons. We have listed down some of these reasons that explain the advantages of the sampling method. 

  1. Can accurately represent the target population as quotas are assigned in order to ensure the final quota sample is representative of the population.
  2. Is a quicker and cheaper method of sampling in comparison to probability sampling methods as elements are chosen using convenience or judgment after quotas are assigned.
  3. Useful when minority participation is critical in the study as all targeted groups will be represented in the sample group. 
  4. You have control over the survey. Quota sampling allows you to monitor who takes the survey and also the number of participants for each quota sample. 

Affordability and ease are enough advantages to categorize it as an effective sampling method. However, there are some challenges that we will discuss next.

What are the disadvantages of quota sampling?

Here are some of the weaknesses of this type of sampling you need to keep in mind when you conduct research. 

  1. Not easily generalizable to the population as elements are chosen from the subgroups based on judgment/convenience hence not taking into account the standard deviation of characteristics among these subgroups.
  2. The inability to calculate sampling error is a disadvantage of all non-probability sampling methods.
  3. High potential for sampling bias with the use of convenience or judgemental sampling to pick the final sample group.

You may have to create additional quota samples to ensure each group is exclusive and there is overlap. However, this can increase the sample size which will lead to more time and money spent on the research.

Wrapping up;

This sums up all you need to know about this sampling method. To recap, as the definition of quota sampling goes, you use your personal judgment to select the final quota sample for the project. While this may create sampling error, you can always examine it using online survey software.

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Hindol Basu 
GM, Voxco Intelligence

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