Quota Sampling Definition: What Is Quota Sampling?

Quota sampling is a non-probability sampling technique that targets a population of interest. It stands in contrast to probability sampling methods like simple random sampling, which uses random selection to pick respondents from the whole population. Whereas all members of a population have an equal chance of getting picked for a study that uses a random sampling method, the likelihood of getting picked for a study that uses quota sampling depends on whether they have certain characteristics. In this way, quota sampling intentionally displays selection bias toward specific groups. It is a popular technique in survey research.

Quota sampling is used when researchers want a representative sample of a target population. For an example of quota sampling, imagine a shoe company conducting market research for its new athletic sneaker. Years of sales data have already identified its core customer demographic: men in the eighteen-to-twenty-five age range with an education level ranging from high school diploma to bachelor's degree.

Thanks to this detailed accuracy, the shoe company can develop a quota sampling methodology to gauge these young men's impressions of its new sneaker. By limiting its sampling frame to people known to engage with its products, the company streamlines its data collection and can better target its forthcoming marketing campaigns. In this scenario and many others like it, the quota sampling method saves researchers time and resources as they seek a final sample to study.

Quota sampling features several core characteristics.

1. 1. It is a form of purposive sampling. Also known as subjective sampling, judgment sampling, expert sampling, or selective sampling, purposive sampling rests on the theory that sometimes researchers must pre-select subgroups from an entire population in order to create a case study or shape a grounded theory.
2. 2. It seeks to replicate real-world population proportions. When researchers use quotas to sample respondents, they often try to scale their data to match the demographics of a real-world population.
3. 3. It can be a form of convenience sampling. Convenience sampling sources respondents based convenience for the researcher. This can lead to fast, low-cost surveys, but it can also lead to sampling errors and researcher bias.
4. 4. It shares some characteristics with stratified sampling. Stratified sampling breaks sample groups into strata, or subsets, that have homogeneous traits. Quota sampling can do the same thing, where the members of a subet all share the same characteristics.

The advantages of quota sampling include the ability to target populations, the ability to scale results to match real-world population proportions, and a relatively low cost compared to probability sampling methods like simple random sampling, systematic random sampling, or stratified random sampling.

The downside to quota sampling is that, as a form of non-probability sampling, it is vulnerable to researcher bias. Researchers can make poor inferences about the population at large, which can lead to surveying the wrong types of people and getting less accurate data than might be gleaned from random sampling. This helps explain why quota sampling is far more prevalent in market research than it is in medical testing, where random trials are crucial for testing the true efficacy of treatments.

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