
Exponential Regression
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We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.
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Get started with Voxco’s ultimate guide to sampling methods
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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.
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.
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.
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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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.
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.
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.
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.
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.
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.
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.
Affordability and ease are enough advantages to categorize it as an effective sampling method. However, there are some challenges that we will discuss next.
Here are some of the weaknesses of this type of sampling you need to keep in mind when you conduct research.
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.
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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