Quota sampling is a non-probability sampling technique where researchers select a convenience sample of people who are representative of the population. These people were selected by researchers based on certain characteristics.
In order for the market research samples to be helpful in gathering data, they determine and set quotas. These samples are generalizable to the entire population. Only the interviewer’s or researcher’s knowledge with the population will determine the final subset.
For instance, let’s consider a scenario where a cigarette company wishes to understand the brand preferences of different age groups in a particular city.
For instance, a tobacco company is interested in understanding the preferences for different cigarette brands among various age groups in a specific city. They set up a survey quota for different age ranges, such as 21-30, 31-40, 41-50, and 51 years and older. This method helps the researcher analyze the smoking trends within the city’s population.
Example of quota sampling
Suppose a researcher wants to conduct a survey on smartphone brand preferences in the United Kingdom. The researcher plans to survey 500 respondents across ten selected states. The quotas are determined as follows:
- Gender Quota:
- 250 males
- 250 females
- Age Quota:
- 100 respondents aged 16-20
- 100 respondents aged 21-30
- 100 respondents aged 31-40
- 100 respondents aged 41-50
- 100 respondents aged 51 and above
- Employment Status Quota:
- 350 employed individuals
- 150 unemployed individuals
- 100 students
- 50 non-students
- Location Quota:
- 50 respondents per state (across ten selected states)
The researcher can use quotas based on the sampling frame, tailored to the research needs. It’s not mandatory to divide quotas evenly. For instance, the researcher may interview 350 employed and only 150 unemployed individuals as needed. Random sampling can also be employed to reach out to respondents.
Types of quota sampling
Quota sampling can be categorized into two types: controlled quota sampling and uncontrolled quota sampling.
Controlled Quota Sampling
The researcher’s selection of samples is constrained by user-controlled quota sampling. The researcher is only able to select samples here.
Uncontrolled Quota Sampling
Uncontrolled quota sampling allows the researcher to select sample members freely, without any imposed restrictions on their choices.
How to conduct quota sampling?
Probability sampling techniques have specific rules for forming samples, unlike quota sampling, which is a non-probability technique without formal rules for sample creation. Quota sampling typically involves four steps to form a sample.
Here are the steps:
1. Divide the Sample Population into Subgroups:
Begin by dividing the entire population into distinct subgroups based on relevant characteristics. These subgroups should be mutually exclusive, meaning each individual belongs to only one subgroup.
Unlike stratified random sampling where subgroups are selected randomly, in quota sampling, the researcher may choose the subgroups based on specific criteria or attributes relevant to the research. In this case, the researcher uses random selection.
2. Determine the Weightage of Subgroups
Evaluate the proportion or weightage of each subgroup within the overall population. This proportion reflects how prevalent each subgroup is in the population. It’s essential to maintain this proportion when selecting samples using quota sampling.
Subgroup analysis is essential for optimizing healthcare outcomes by tailoring treatments for particular patient groups.
For instance, if a certain age group represents 58% of potential customers for Bluetooth headphones, ensure that your sample reflects this percentage for that age group.
3. Select an Appropriate Sample Size
Based on the proportions determined in the previous step, choose an appropriate sample size that reflects these proportions. For example, if your target population is 500 individuals, and a certain subgroup represents 20% of the population, your sample from that subgroup should also be 20% of the total sample size.
4. Conduct Surveys According to Defined Quotas
To get real, actionable results, make sure you stick to the predefined quotas. Avoid filling up survey quotas; instead, concentrate on finishing surveys for each quota.
When to use Quota Sampling?
Quota sampling is best used in research designs, both qualitative and quantitative, to get into specific characteristics of particular subgroups or to explore relationships among different subgroups.
It proves particularly effective when there’s no clear sampling frame available, allowing researchers to obtain a sample that represents the population being studied as closely as possible.
It’s important to note that quota sampling only reflects the responding sample, limiting its ability to generalize findings to the broader population. This method also carries a higher risk of research bias compared to probability sampling.
Quota sampling is helpful for getting a comprehensive view of attitudes, behaviors, or situations, like understanding various concerns people have about a topic. It’s also beneficial when respondents come from diverse sources, such as random pop-up surveys, street surveys, website-embedded surveys.
Quota sampling can be completed very quickly because it doesn’t demand a significant time or financial investment. Consider using quota sampling as a good method if you need results quickly.
characteristics of quota sampling
Here are the top characteristics of quota sampling:
- Quota sampling aims to obtain the best representation of respondents in the final sample, reflecting the diversity of the population.
- Quotas in quota sampling replicate the characteristics of the population of interest, providing a real-world representation.
- The estimates derived from quota sampling are more representative of the population due to the deliberate selection of quotas.
- The quality of quota samples can vary depending on the accuracy and appropriateness of the quotas chosen by the researcher.
- Quota sampling can save time in data collection since the sample is designed to represent the population, reducing the need for extensive sampling.
- If the quotas accurately represent the population, quota sampling can lead to cost savings in research, as fewer resources may be required for data collection.
- Quota sampling allows researchers to monitor the number and types of individuals included in the survey, ensuring a balanced sample composition.
- Researchers always divide the population into subgroups based on specific characteristics or traits relevant to the research.
- The sample obtained through quota sampling is designed to represent the entire population, providing insights into broader trends and patterns.
- Researchers use quota sampling to identify and analyze the traits of specific groups within the population, helping to understand variations and preferences among different segments.
benefits of quota sampling
Here are the benefits of quota sampling:
- Time-Saving: Quota sampling saves time in the sampling process because quotas are used to create samples quickly and efficiently. Researchers can target specific subgroups without needing to sample the entire population.
- Accurate Representation: Researchers that use this sampling technique are able to accurately represent a population. Overrepresentation cannot occur since this sampling technique uses predetermined quotas to assist researchers in studying the population.
- Cost-Effective: Quota sampling is cost-effective because it requires minimal resources and budget compared to other sampling methods. Researchers can achieve representative samples without extensive data collection efforts, leading to cost savings in research projects.
- Research Convenience: It is significantly easier for a researcher to evaluate data and survey responses when they use quota sampling and appropriate research questions.
applications of quota sampling
Here are the applications of quota sampling:
- Specific Research Criteria: Quota sampling is applied when researchers have specific criteria for their research, allowing them to select subgroups based on particular traits or characteristics. This method enables researchers to obtain desired results by filtering subgroups according to the research criteria.
- Non-Precision Research Studies: Due to the nature of the research studies, certain investigations don’t require project accuracy. It is ideal for quota sampling in these studies.
- Time Constraints: Researchers use quota sampling when they have limited time for data collection. By applying quotas, researchers can quickly gain insights into the entire population of interest within a short time frame.
- Budget Constraints: Quota sampling is utilized in research projects with tight budgets. Instead of studying a large population, researchers can save money by using quotas to capture the overall population’s characteristics effectively.
Limitations of Quota sampling
Quota sampling comes with several limitations:
- High Bias Potential: Due to its non-random sample selection process, quota sampling can introduce bias into the sample, leading to less reliable data. This bias can stem from factors such as the researcher’s judgment or the respondent’s characteristics.
- Lack of Generalizability: While quota sampling can accurately represent the characteristics defined by quotas, it may not capture other crucial characteristics present in the population. This limitation restricts the generalizability of findings beyond the specific quotas used in the sampling process.
- Inability to Calculate Sampling Error: Quota sampling is not a probability sampling method, which means researchers cannot calculate the sampling error associated with their data. This absence of sampling error calculation limits the ability to assess the accuracy and precision of the results obtained through quota sampling.