Quota sampling is a non-probability sampling method where researchers select participants based on predefined quotas representing key population characteristics, such as age or gender. Unlike random sampling, it doesn’t give every individual an equal chance of selection but ensures specific subgroups are represented. This method is quick, cost-effective, and useful for market research and social studies. Controlled quota sampling adds structure to reduce bias, while uncontrolled quota sampling offers speed and flexibility. However, because participant selection isn’t random, results may suffer from sampling bias and limited generalizability. Despite this, quota sampling remains practical for studies needing balanced subgroup representation.
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Quota Sampling Definition
A quota is a “fixed minimum or maximum number of a particular group of people allowed to do something.” Therefore, we define quota sampling as “a non-probability sampling method that relies on the non-random selection of a predetermined number or proportion of units, called a quota.” Quota sampling is a non-probability sampling technique, and the quota sampling method is often used when researchers want to ensure certain groups are represented. Proportional quota sampling is a method that ensures the sample maintains the same proportions as the population across various subgroups.
To better understand the definition of quota sampling, it helps to know the difference between probability sampling and non-probability sampling.
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Probability sampling means that the sample population is selected randomly, and every individual has an equal chance of being selected.
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Non-probability sampling means that the sample population is selected purposefully, and not everyone has an equal chance of being selected. There are other sampling methods, such as stratified sampling and cluster sampling, which differ from quota sampling in their use of randomization and sampling frames.
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This means that quota sampling provides researchers with some control over certain aspects of their sample selection. In controlled sampling, there are some limitations, while in uncontrolled sampling, there are no restrictions. Either way, because the researcher is in some ways controlling the sample, it cannot be applied to the wider population, and there is a high risk of survey bias being introduced. In other sampling methods, a sampling frame—a comprehensive list or database of the population—is often used to ensure representativeness, but quota sampling may not require a complete sampling frame. We’ll discuss all of this shortly.
How to Conduct Quota Sampling Method
Although quota sampling has no formal rules or proportions, understanding the sampling process is essential. To perform quota sampling, follow these four steps:
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Divide the sample population into subgroups. Divide the population into distinct subgroups based on specific characteristics such as gender, age, employment status, or location. These mutually exclusive subgroups could be as simple as men and women, or more complex with multiple subgroups.
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Select an appropriate sample size. A small business determines they have 1000 customers and chooses to sample 10% of them, so 100 people total.
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Determine the weightage of subgroups. This means evaluating the proportion in which the subgroups exist in the population. For each subgroup, set specific quotas to ensure proportional representation. For example, a store determines its customer base of 1000 is comprised of 600 women and 400 men.
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Sample based on proportion. The quota size should be representative of the collective subgroup population. In the example above, they should select 60 women and 40 men. These are the quotas.
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Quota sampling facilitates efficient data collection and helps researchers collect data from targeted subgroups, making it a practical approach for market research and social studies.
Types of Quota Sampling
Quota sampling is a versatile non-probability sampling method that can be tailored to fit different research needs. When researchers use this sampling method, they can choose between two main types: controlled quota sampling and uncontrolled quota sampling. Understanding these types helps clarify how quota samples are selected and managed, and how they differ from probability sampling methods.
Controlled quota sampling is a more structured approach. In this type of quota sampling, the researcher sets specific criteria and guidelines for selecting participants within each subgroup. For example, if a study requires a certain number of respondents from different age groups, the researcher might also specify that participants must be selected from various locations or at different times of day. This added control helps ensure that the final sample more closely matches the target population’s characteristics, reducing the risk of sampling bias. While controlled quota sampling is still a non-probability sampling method—meaning not all population members have an equal chance of selection—it does offer more oversight than other non-probability sampling techniques.
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Uncontrolled quota sampling on the other hand, is much more flexible. Here, the only requirement is to fill the predetermined quotas for each subgroup, without any additional restrictions on how participants are chosen. For instance, a researcher might simply survey the first people who meet the basic subgroup criteria until the quota is filled. This approach is quick and convenient, but it increases the risk of sampling error and bias, since the selection process is less systematic and may not accurately represent the entire population.
Both types of quota sampling rely on non-random selection, setting them apart from probability sampling methods like stratified sampling or simple random sampling. While controlled quota sampling offers more structure and can help ensure adequate representation of important characteristics, uncontrolled quota sampling is often used when speed and convenience are top priorities.
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By understanding the different types of quota sampling, researchers can choose the sampling technique that best fits their research objectives, timeline, and available resources.
Example of Quota Sampling
To clarify the concept, let’s look at some quota sampling examples and examples quota sampling that illustrate how this method works in practice.
An example of quota sampling in the real world is the best way to understand how it works. First, consider that in other types of sampling using randomization, a researcher may take their entire customer list of 1000, assign numbers to each customer, and then use a random number generator to select a sample of 100. The result is completely random, with all 1000 customers having an equal chance of selection.
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With quota sampling, a researcher may have a quota of 60 women and 40 men, or may set quotas based on other demographic variables such as employment status. For instance, the researcher could aim to survey 30 employed individuals and 30 unemployed individuals, in addition to gender quotas. Pop-up surveys are a common way to quickly gather responses for quota sampling, especially when targeting people as they enter a store or visit a website. So, the researcher stands outside the store and surveys the first 60 women and 40 men, or the required number of people in each employment status group, who come into the store. Boom, done! It’s that easy. But be sure to read on to learn the biggest disadvantage of this sampling technique.
Quota Sampling Advantages and Disadvantages
The advantages of quota sampling include its ability to efficiently gather representative data from specific subgroups, making it a popular choice in various research projects and market research studies.
Quota sampling has many advantages, and one drawback that could seriously make a researcher reconsider using this method.
One of the main advantages of quota sampling is that it saves both time and money. By focusing on specific subgroups, researchers can collect targeted data more quickly and with fewer resources. This method helps reduce research costs, which is especially beneficial in market research and research projects where budgets may be limited.
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Quota sampling is best used when researchers need to ensure that certain subgroups are adequately represented in their sample. It is commonly applied in research projects and market research to obtain accurate insights into consumer preferences, market segments, and population characteristics.
Benefits of Quota Sampling: Quick, Easy, Inexpensive, and Produces a Representative Sample
Quota sampling is a time and money saver and is often used by researchers working within a tight timeline or budget. Because there’s no need for randomization or strict requirements in place, quota sampling is a simple way to get some usable results. Analysis after the survey is also usually more straightforward, which can reduce the need for additional resources.
Quota Sampling Disadvantage: Risk of Sampling Bias
The negative aspect of quota sampling is the potential for sampling bias, which could be a major drawback depending on the type of research being conducted. To see how sampling bias can easily occur with quota sampling, let’s look back at the example of the researcher who stood outside his store to survey men and women.
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This survey may include survey bias in several ways:
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He’s surveying only people who are shopping in his store on one particular day. They could mostly be first-time customers, so the sample doesn’t factor in the opinions of long-time customers.
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By surveying outside the store, he’s excluding the opinions of customers who do the majority of their shopping online.
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He may conduct this survey between the hours of 9 am – 5 pm, when many people are working. So, his sample might mostly consist of unemployed, stay-at-home, or retired customers (and in this case, age could be greatly skewed).
He could introduce his personal bias in several ways:
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He may approach only men and women he thinks look like “high-end” shoppers, which would rule out customers shopping for value.
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He might only approach men and women of a certain race, ethnicity, or age, skewing results to one demographic.
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He might avoid parents with children because they’re busy managing the kids. However, this could limit his sample to mostly people without children who likely have very different shopping habits.
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Conclusion
Quota sampling is an easy and efficient way to get some answers from a subset of a larger population. However, because it is not conducted with survey randomization in mind, the threat of survey bias is much larger than in other types of surveys. It’s up to the researcher to weigh the pros and cons of quota sampling, and then it’s on with the surveys!
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Which types of sampling do you usually use? Do you use quota sampling? Is there another method of sampling you prefer, and if so, why? Let us know in the comments!
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Frequently Asked Questions (FAQs)
What is quota sampling?
Quota sampling is known as “a non-probability sampling method that relies on the non-random selection of a predetermined number or proportion of units, called a quota.”
What are the advantages and disadvantages of quota sampling?
Quota sampling is a quick, easy, and inexpensive way to get survey results. The one drawback is that because of the lack of randomization, there is a greater potential for survey bias.
What types of quota sampling are there?
Two types: Controlled sampling, which has some sampling restrictions, and uncontrolled sampling, which has none.
