Quota Sampling Calculator
Calculate the number of survey responses needed from each population stratum using proportional quota sampling. Ensures your sample mirrors the population composition.
About this calculator
This calculator splits a total sample size across up to four population strata in proportion to each stratum's share of the combined population (line 10), rounding each stratum's raw share to a whole quota (lines 21-24). Because rounding four shares independently can leave the quotas one or two respondents short of — or over — the target, the calculator computes the shortfall and adds or subtracts it entirely from whichever stratum currently has the largest quota (lines 27-34), so the four quotas always resum to exactly the Total Sample Size you entered, regardless of how the population is split. Nothing here happens if every stratum's population is 0: the whole allocation block is skipped by an explicit `totalPopulation > 0` guard (line 15), leaving all four quotas and percentages at 0 rather than dividing by zero.
A quirk worth knowing before you rely on this for planning: typing 0 into Total Sample Size does not zero out your quotas the way typing 0 into a stratum's population does — `inputs.totalSample || 1` (line 4) reads a literal 0 as missing and substitutes 1, so you'd instead get a 1-person sample split across strata. What this does not account for: minimum viable cell sizes per stratum, non-response adjustment, or any weighting scheme other than population share — every stratum here competes for quota purely by its share of the combined population you enter.
Inputs
Results
Stratum 1 Quota
500
How to Use This Calculator
- Enter your target total sample size.
- Define the quota strata (age groups, gender, region) and the target percentage for each.
- Input the number of completed interviews in each stratum so far.
- Review the Quota Fill Rate and the Remaining Completes Needed per stratum.
- Close quotas that are full and focus recruitment on underrepresented groups.
How the result changes with Total Sample Size
| Total Sample Size | Stratum 1 Quota |
|---|---|
| 500 | 250 |
| 750 | 374 |
| 1,500 | 750 |
| 2,500 | 1,250 |
What each input means
- Total Sample Size
- The total number of survey responses you plan to collect across all strata.
- Stratum 1 Population
- Population count for stratum 1 (e.g., age 18-34 or region A). Used to calculate proportional quota.
- Stratum 2 Population
- Population count for stratum 2 (e.g., age 35-54 or region B).
- Stratum 3 Population
- Population count for stratum 3 (e.g., age 55-64 or region C). Set to 0 if unused.
- Stratum 4 Population
- Population count for stratum 4 (e.g., age 65+ or region D). Set to 0 if unused.
How this is calculated
Worked example, using the default values
- Identify Input Parameters4 parametersTotal Sample Size = 1000, Stratum 1 Population = 50000, Stratum 2 Population = 35000, Stratum 3 Population = 10000 = 5 input(s) provided
- Calculate Stratum 1 QuotaStratum 1 Quota500 = 500
- Calculate Stratum 2 QuotaStratum 2 Quota350 = 350
- Calculate Stratum 3 QuotaStratum 3 Quota100 = 100
Engine last updated . Checked against 2 independently-derived tests — how we verify calculators. Built by Paul Gunder, a software engineer, not a licensed financial, medical, or legal professional.
Frequently Asked Questions
Why do the four stratum quotas always add up to exactly the Total Sample Size?
Rounding each stratum's proportional share independently (lines 21-24) can leave the four quotas summing to one or two more or fewer than the target, so the calculator measures that shortfall and pushes it entirely onto whichever stratum's quota is currently largest (lines 27-34) — by default that's Stratum 1, since its population of 50,000 is the biggest of the four. The correction guarantees an exact match regardless of how the population is split across strata.
What happens if I type 0 into Total Sample Size instead of leaving the default?
It doesn't zero out the quotas. The line reading it is `inputs.totalSample || 1` (line 4), and JavaScript's `||` treats a literal 0 as absent, substituting 1 instead — so a 0 entry quietly becomes a 1-person total sample split proportionally across your strata, not an empty allocation.
Does increasing one stratum's population change the quotas for the other strata?
Yes. Every stratum's quota is that stratum's population divided by the combined population of all four (line 10), so growing Stratum 1's population dilutes every other stratum's share of the total and lowers their quotas even though their own population figures never changed — the four strata are competing for a fixed Total Sample Size.
How does proportional quota sampling here compare to allocating quotas by hand using target percentages?
Many researchers set quotas manually by assigning a target percentage to each stratum rather than deriving it from raw population counts, which lets them deliberately oversample a rare-but-important group instead of matching the population exactly. This calculator only supports proportional allocation from the population figures you enter -- if your study design calls for disproportionate stratification, you'll need to compute those quotas separately rather than relying on the population-share method built into this tool.
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