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Quota Sampling: Definition, Method and Examples

By Julia Simkus, published Jan 07, 2022

Quota sampling is a type of non-probability sampling where researchers will form a sample of individuals who are representative of a larger population.

Non-probability sampling means that researchers choose the sample as opposed to randomly selecting it, so not all members of the population have an equal chance of participating in the study.

Key Terms
  • A sample is the participants you select from a target population (the group you are interested in) to make generalizations about. As an entire population tends to be too large to work with, a smaller group of participants must act as a representative sample.
  • Representative means the extent to which a sample mirrors a researcher's target population and reflects its characteristics (e.g. gender, ethnicity, socioeconomic level). In an attempt to select a representative sample and avoid sampling bias (the over-representation of one category of participant in the sample), psychologists utilize a variety of sampling methods.
  • Generalisability means the extent to which their findings can be applied to the larger population of which their sample was a part.

Researchers will assign quotas to a group of people in order to create subgroups of individuals that represent characteristics of the target population as a whole.

Some examples are these characteristics are gender, age, sex, residency, education level, or income. Once the subgroups are formed, the researchers will use their own judgment to select the subjects from each segment to produce the final sample.

It is important for researchers to maintain the correct proportions to represent the population. For example, if the larger population is 65% female and 35% male, the final sample should reflect these percentages.

Types of quota sampling

  1. Controlled Quota Sampling
    • In controlled quota sampling, there are limitations on the researcher’s choice of samples.
  2. Uncontrolled Quota Sampling
    • In uncontrolled quota sampling, there are no restrictions on the researcher’s choice of samples. Researchers are free to choose sample members at their own will.

Applications: When is it used

Quota sampling is used when…

  • time is limited as quota sampling is a quick method of sampling.
  • budget is tight as it is a cheaper method than other sampling methods.
  • researchers have specific criteria or constraints for conducting their research.
  • researchers want to monitor the number of participants that are allowed to complete a survey depending on characteristics such as age, gender, or race.
  • researchers do not have access to an entire population.

How to quota sample?

  1. Divide the sample into subgroups depending on any relevant characteristics. For example, you could divide a university population by major.
  2. Evaluate the proportions of the subgroups to determine the specific elements that will be chosen from each quota. For example, engineering students might be ⅕ of the population.
  3. Select a sample size. For example, if you are sampling 8,000 students, your quota sample might be 100.
  4. Choose your participants, adhering to the subgroups characteristics. For example, 20% of your sample should be engineering students.
  5. Continue with the selection process until your quotas are filled.   


Quick and easy

Because the sample is representative of the population of interest, quota sampling saves data collection time. It is a quick, straightforward, and convenient way to sample data.


The research costs for this method of sampling are minimal. Researchers save money by using fewer quotas to represent the whole population rather than sampling every individual of a larger population.

Representative of target population

The goal of quota sampling is to replicate the population of interest. Researchers will aim to form a sample that effectively represents the population’s characteristics.


Large potential for bias

Because this method involves non-random sample selection, samples can be biased, making the data less reliable.

Not generalizable to the population

While this sampling method can be very representative of the quota-defining characteristics, other important characteristics may not be represented in the final sample group.

Cannot calculate sampling error

Because quota sampling is not a probability sampling method, researchers are unable to calculate the sampling error.


  • Ensuring that an adequate number of midlife women were recruited from the targeted ethnic groups in an Internet based study (Im & Chee, 2011).
  • Recruiting at-risk Women for microbicide research and ensuring adequate representation of specific sample characteristics (Morrow et al., 2007).
  • Obtaining a representative sample of pregnant women to study trends in smoking during pregnancy in England (Owen, McNeill, & Callum, 1998).
  • Recruiting respondents to participate in an interview about stress levels with quotas based on sex, age, working status, residential location, housing tenure, and ethnicity (Sedgwick, 2012).
  • Monitoring national trends of tobacco smoking in France (Guignard et al., 2013).
  • Quantifying the use of sunbeds in children across England and identifying geographical variation to study the rise of malignant melanoma (Thomson et al., 2010).

Quota Sampling vs Stratified Sampling

Quota sampling and stratified sampling both involve dividing a population into mutually exclusive subgroups and sampling a predetermined number of individuals from each.

However, the most significant difference between these two techniques is that quota sampling is a non-probability sampling method while stratified sampling is a probability sampling method.

In a stratified sample, individuals within each stratum are selected at random while in a quota sample, researchers choose the sample as opposed to randomly selecting it.

About the Author

Julia Simkus is an undergraduate student at Princeton University, majoring in Psychology. She plans to pursue a PhD in Clinical Psychology upon graduation from Princeton in 2023. Julia has co-authored two journal articles, one titled “Substance Use Disorders and Behavioral Addictions During the COVID-19 Pandemic and COVID-19-Related Restrictions," which was published in Frontiers in Psychiatry in April 2021 and the other titled “Food Addiction: Latest Insights on the Clinical Implications," to be published in Handbook of Substance Misuse and Addictions: From Biology to Public Health in early 2022.

How to reference this article:

Simkus, J. (2022, Jan 07). Quota Sampling: Definition, Method and Examples. Simply Psychology.


Boston University School of Public Health. (n.d.). The role of probability. Sampling. Retrieved from

Guignard R, Wilquin J-L, Richard J-B, Beck F (2013) Tobacco Smoking Surveillance: Is Quota Sampling an Efficient Tool for Monitoring National Trends? A Comparison with a Random Cross-Sectional Survey. PLoS ONE 8(10): e78372.

Im, E. O., & Chee, W. (2011). Quota sampling in internet research: practical issues. CIN: Computers, Informatics, Nursing, 29(7), 381-385.

Morrow, K.M., Vargas, S., Rosen, R.K. et al. (2007). The Utility of Non-proportional Quota Sampling for Recruiting At-risk Women for Microbicide Research. AIDS Behav 11, 586.

Owen, L., McNeill, A., & Callum, C. (1998). Trends in smoking during pregnancy in England, 1992-7: quota sampling surveys. Bmj, 317(7160), 728-730.

Quota sampling: Definition, types & free examples. QuestionPro. (2021, July 19). Retrieved from

Quota Sampling. Voxco. (2021, March 12). Retrieved from

Sedgwick, P. (2012). Proportional quota sampling. BMJ, 345.

Thomson, C. S., Woolnough, S., Wickenden, M., Hiom, S., & Twelves, C. J. (2010). Sunbed use in children aged 11-17 in England: face to face quota sampling surveys in the National Prevalence Study and Six Cities Study. Bmj, 340.

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