Forms · Glossary
What is quota sampling?
Quota sampling is a non probability method in which a researcher sets target numbers for groups, such as age bands or regions, matching their share of the population, then recruits people until each quota is full. Selection within each group is not random, so the sample can look representative while still missing people who are harder to reach.
Quota samples are fast and cheap, which is why most online panels use some form of them. They control who is counted, but not who is willing to answer.
Indunil Asanka · Co-founder
4 min read · Published
| Age band | Share of adult population | Quota | Completed so far |
|---|---|---|---|
| 18 to 34 | 30% | 120 | 120, closed |
| 35 to 54 | 34% | 136 | 131 |
| 55 to 74 | 26% | 104 | 104, closed |
| 75 and over | 10% | 40 | 22 |
How quota sampling works
The researcher picks a few characteristics known for the population, such as age, gender and region from census figures, and sets quotas in proportion. Interviewers or an online panel then recruit anyone who fits until each quota is reached, at which point people in that group are screened out. In the worked example, the survey of 400 adults has filled its youngest and middle aged quotas but is still short of people aged 75 and over, a common pattern because older adults are less present on online panels.
Quota sampling and stratified sampling
Both divide the population into groups and fill each in proportion. The difference is selection within each group. In stratified sampling, people are drawn at random from a list of each stratum, so the laws of probability apply and margins of error can be calculated. In quota sampling, whoever is convenient and willing fills the quota. The American Association for Public Opinion Research's task force on non probability sampling describes quota methods as a form of non probability sampling and warns that their accuracy depends on assumptions that cannot be checked from the sample alone.
Why it is used anyway
Random samples need a sampling frame, a list of everyone, and they are slow and expensive, with low response rates. Quota samples can be collected quickly from an online panel. Pew Research Center's 2016 comparison of online non probability samples found their accuracy varied widely between vendors, and its 2018 work on weighting found that adjusting on more variables than the quotas used improved estimates but did not remove all bias.
Common mistakes
Setting quotas on a few variables and assuming the sample matches on everything else. Filling quotas with the first people to respond, who are often the most interested in the topic. Reporting a margin of error as if the sample were random. And leaving a quota half filled, then weighting the few respondents in it heavily, which magnifies their individual quirks.
Quotas and a OneCraft form
A OneCraft form can carry the screening questions, such as age band and town, as required choice fields, and responses export to CSV with one column per field so quota counts can be tracked in a spreadsheet. The form does not count quotas or close itself when a group is full; that tracking happens outside it, or in the panel that sends people to the form.
Questions people ask
Is quota sampling random?
No. Quotas control how many people come from each group, but who fills each quota is decided by availability and willingness, not chance. That is the defining difference from probability methods such as simple random or stratified sampling, and it is why standard margins of error do not strictly apply to quota samples.
When is quota sampling appropriate?
When speed and cost matter more than formal precision, such as concept testing, early market research or tracking that compares results over time with the same method. It is less suited to estimates that must stand up statistically, such as official statistics or a prevalence figure that will drive funding decisions.
What variables should quotas use?
Ones that are known for the population and likely to relate to the answers, such as age, gender, region and sometimes education or income. Using variables strongly linked to the topic, for example car ownership in a transport survey, helps more than adding many unrelated quotas.
Can quota samples be weighted?
Yes, and they usually are, to correct small imbalances or to adjust on variables that were not part of the quotas. Weighting cannot fix groups the sample barely reached. Pew Research Center found that weighting on more variables improved accuracy but left some bias in place.
What is the difference between quota sampling and convenience sampling?
Convenience sampling takes whoever is easiest to reach with no controls. Quota sampling also takes accessible people but caps how many come from each group, so the sample matches the population on the quota variables. It is convenience sampling with structure, still non random within each group.
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Create a form with OneCraftRelated questions
- What is stratified sampling?Stratified sampling splits a population into groups, called strata, and samples each one. A worked staff survey example, proportionate and disproportionate.
- What is convenience sampling?Convenience sampling surveys whoever is easiest to reach, such as passers by or a shared link. Why it is quick, where its bias comes from, when it is enough.
- What is a representative sample?What is a representative sample? One that mirrors the population on the traits that shape the answers. Random, stratified, convenience and quota compared.
- What is survey weighting?What is survey weighting? Adjusting responses so the sample matches the population. A raw vs weighted worked example, the main methods, and its limits.
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