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Statistics · Statistical sampling

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Non-random sampling — quota and opportunity

The two sampling methods that don't use chance: quota sampling (fill preset quotas for each group, choosing respondents non-randomly) and opportunity (or convenience) sampling (use whoever is available). How they work, when they're used, and why quota is not the same as stratified sampling.

Statistics · Statistical sampling

Non-random sampling — quota and opportunity

The two sampling methods that don't use chance: quota sampling (fill preset quotas for each group, choosing respondents non-randomly) and opportunity (or convenience) sampling (use whoever is available). How they work, when they're used, and why quota is not the same as stratified sampling.

Why it works

Sometimes you have no sampling frame, or no time to build one, so a random method isn't available. Non-random sampling lets a person — not chance — pick the sample. It's quick and cheap, but because human choice is involved it risks bias: not every unit has a known chance of selection.

Quota sampling. The researcher decides in advance how many to collect from each group — the quotas — chosen to reflect the population (e.g. "interview 2020 men and 2020 women"). They then approach people and slot them into the quotas until each is full, choosing who to ask themselves. No sampling frame is needed, which is why market researchers use it on the street.
  • Advantages: no sampling frame required; cheap and quick; works even for a small
population or hard-to-reach groups; keeps the group proportions of the population.
  • Disadvantages: it is non-random, so it can be biased — the interviewer
chooses who to approach (and may avoid some people), and non-responders are just replaced, so not every unit has a known chance of selection.

Opportunity (convenience) sampling. You sample whoever is available at the time and fits the criteria — for instance, asking the first 3030 people who walk past, or the classmates who happen to be in the room. It is the easiest method of all.
  • Advantages: very easy, cheap and quick to carry out.
  • Disadvantages: unlikely to be representative — it depends entirely on *who
happens to be there and when*, so it's wide open to bias and conclusions may not generalise to the population.

The exam's favourite trap: quota is not stratified. They sound alike because both split the population into groups, but the selection differs:
  • Stratified is random — you need a sampling frame and take a *simple random
sample* within each stratum.
  • Quota is non-random — you need no frame and the interviewer chooses
who fills each quota.

So if a question says respondents were picked at the researcher's discretion until the numbers were met, it's quota, not stratified — even though the group sizes look the same.