Quota sampling

Quota sampling is where we divide the population into groups and then sample from each group separately based on convenience (opportunity sampling).

Quota sampling is identical to stratified sampling except that instead of sampling from each group at random, we sample based on convenience.

For example, if we’re surveying people in a shopping mall, we might divide the population into groups based on age and gender, and then survey people from each group as they walk past us - without trying to select them at random.

This method is easier than stratified sampling, but it can give us a less representative sample, if the people who happen to walk past aren’t representative of the group as a whole.

See stratified sampling for a full explanation of how the groups are made and how we know how many people to survey from each group.

Advantages of quota sampling

• It can be easier than stratified sampling, especially if there are many groups.
• It can allow us to make comparisons between groups.
• It lets us ensure that we have enough people from each group in our sample, which can be important if some groups are small.
• It means that a single group can’t dominate the sample, which can happen with simple random sampling if you get unlucky.

Disadvantages of quota sampling

• It can give us a less representative sample than stratified sampling, if the people who happen to walk past aren’t representative of the group as a whole.
• We need to know some things about the population first, which can be difficult or expensive to find out.
• If we don’t divide the population into the right groups, we might not get a representative sample. For example, if we divide the population into groups based on age and gender, but the important differences are actually based on income, then we might not get a representative sample.
• If we don’t sample from each group in the right proportions, we might not get a representative sample. For example, if we sample too many people from one group and too few from another, we won’t get a representative sample.
• It can be more work than simple random sampling, especially if there are many groups.