Quota sampling is a non-probability sampling method in which researchers divide a population into subgroups (strata) and set quotas for how many respondents from each subgroup must be included in the sample, ensuring specific characteristics are represented at predetermined levels.
How Quota Sampling Works
In quota sampling, the researcher identifies the key characteristics they want the sample to reflect (age, gender, region, income band) and sets targets for each subgroup. Data collection continues until all quotas are filled. For example, a study of 1,000 UK adults might set quotas of 500 men and 500 women, further divided into age bands reflecting the national age distribution.
Unlike stratified random sampling, quota sampling does not randomly select respondents within each stratum - the researcher or fieldwork panel accepts any respondent who fits the quota requirements until the target is reached. This makes quota sampling a non-probability method, which affects how findings can be reported and generalised.
Proportional vs Non-Proportional Quotas
Proportional quota sampling sets quotas that reflect the true proportions of each subgroup in the population. If 55% of the population is female, the quota sample should be 55% female.
Non-proportional quota sampling deliberately oversamples some subgroups to ensure sufficient cell sizes for subgroup analysis. Results from non-proportional samples must be weighted before reporting at the total level.
Quota vs Random Sampling
Quota sampling is faster and less expensive than probability sampling because it does not require a sampling frame and allows fieldwork to stop as soon as quotas are filled. These advantages make it the dominant method in commercial market research.
The limitation is that quota samples cannot be used to calculate formal statistical confidence intervals, because the selection within quotas is not random. Academic research requiring these properties typically uses probability-based sampling methods.
Frequently Asked Questions
Quota sampling produces reliable and consistent results for tracking and comparison purposes, but is not technically a probability sample. This means formal statistical tests and margin-of-error calculations based on random sampling theory do not strictly apply.
Quota sampling is used in almost all commercial online panel research. Quotas on age, gender, region, and other demographic variables are set to approximate the target population composition.
Stratified random sampling randomly selects respondents from within each stratum, making it a probability method. Quota sampling accepts any respondent who fits the stratum requirements until the quota is filled, making it a non-probability method.
Yes. Qualtrics has built-in quota management allowing researchers to set quotas by response value, embedded data, or demographic variables. When quotas are filled, Qualtrics automatically screens out or redirects respondents who would exceed the quota limits.
Deploy Your Survey to 27+ Platforms
Convert Word, PDF, and Excel survey instruments to Qualtrics, REDCap, SurveyMonkey, and more. No manual programming required.
Start Converting Free