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API · /samplesize-api

Sample Size API

healthy 3,896 Subscribers

Survey and poll sample-size planning as an API, computed locally and deterministically. The proportion endpoint computes the number of respondents needed to estimate a proportion within a target margin of error at a chosen confidence level, n = z²·p(1−p)/E², defaulting to the worst-case p = 0.5 that maximises the required size, with an optional finite-population correction n/(1 + (n−1)/N) for a known population — the classic ±5 % margin at 95 % confidence needs 385 responses, ±3 % needs 1 068, and capping the population at 1 000 cuts the ±5 % requirement to 278. The mean endpoint sizes a sample for estimating a mean to within a margin of error from the standard deviation, n = (z·σ/E)². The margin endpoint inverts the relationship, returning the margin of error a given sample size actually achieves. The critical z-value is computed from the confidence level with a high-accuracy inverse-normal so any confidence works, not just the textbook 90/95/99 %. Margins, proportions and confidence are decimals (0.05, 0.5, 0.95). Everything is computed locally and deterministically, so it is instant and private. Ideal for market-research, polling, UX-research, survey-platform, product-analytics and statistics-education app developers, study-planning and sample-size tools, and research software. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is sample-size planning with the normal approximation; for A/B-test significance use an A/B-test API and for descriptive statistics a statistics API.

#sample-size #survey #margin-of-error #polling #market-research #developer-tools
api.oanor.com/samplesize-api
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Machine-readable spec so AI agents can integrate this API.

/api/samplesize-api/openapi.json
/api/samplesize-api/llms.txt

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Sample Size API — live data on the oanor API marketplace

API health

healthy
Uptime
100.00%
Server probes · 24h
Avg latency
78 ms
Server probes · 24h
Subscribers
3,896
active
Total calls
76
last 7 days
status Full status page → · 12 probes/24h

Pricing

Pick a tier — billed monthly, cancel anytime.

Free

Free

  • 6,200 calls / month
  • 2 requests / second
  • Hard cap (429 above quota, no overage)
  • 6,200 calls/month
  • 2 req/sec
  • Proportion + mean + margin of error
  • No credit card
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Starter

€5.60 /month

  • 62,000 calls / month
  • 6 requests / second
  • Hard cap (429 above quota, no overage)
  • 62,000 calls/month
  • 6 req/sec
  • Any confidence level, finite population
  • Email support
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Pro

€15.80 /month

  • 280,000 calls / month
  • 15 requests / second
  • Hard cap (429 above quota, no overage)
  • 280,000 calls/month
  • 15 req/sec
  • Survey-platform & research pipelines
  • Priority support
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Mega

€49.50 /month

  • 1,550,000 calls / month
  • 40 requests / second
  • Hard cap (429 above quota, no overage)
  • 1,550,000 calls/month
  • 40 req/sec
  • Platform scale
  • Dedicated SLA
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Inferential-statistics maths as an API, computed locally and deterministically. The samplesize endpoint computes how many respondents a survey or experiment needs for a proportion, n = Z²·p(1−p)/E², from a confidence level and a margin of error (using p = 0.5 for the most conservative size), with a finite-population correction when the population is known. The confidence endpoint builds a confidence interval for a mean (estimate ± Z·σ/√n) or a proportion (p ± Z·√(p(1−p)/n)), returning the standard error, margin of error and the lower and upper bounds. The ztest endpoint runs a one-sample z-test, z = (x̄ − μ₀)/(σ/√n), and returns the z-score, the one- or two-tailed p-value and whether the result is significant at the chosen alpha. The z-scores come from an exact inverse-normal and the p-values from the normal CDF. Everything is computed locally and deterministically, so it is instant and private. Ideal for A/B-testing, survey, research and analytics app developers, experiment dashboards and data-science tools, and education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is inferential statistics; for descriptive statistics use a statistics API and for probability distributions use a probability API.

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Frequently asked questions

Quick answers about pricing, quotas, and integration.

How do I get an API key for Sample Size API?
Sign up for free at oanor.com, generate an API key from the developer dashboard, and call Sample Size API with the x-oanor-key header. No credit card needed for the free tier.
What's the rate limit for Sample Size API?
Free tier allows 1 request per second. Paid plans scale up to 50 requests per second on the Mega tier. Hard limits return HTTP 429 above the quota — no surprise overage charges.
How much does Sample Size API cost?
Sample Size API has a free tier with 100 calls / month. Paid plans start at €5.60 / month with higher quotas and faster rate limits.
Can I cancel my subscription anytime?
Yes. Plans are billed monthly and you can cancel anytime from your billing dashboard. No long-term contracts and no cancellation fee.
Is Sample Size API GDPR-compliant?
All requests to Sample Size API go through our EU-based gateway. Your upstream API key never leaves our server and no personal data is shared with the upstream provider beyond the request you send.

Pick an endpoint from the list on the left to see its details and try it.

Code snippets

Sign up to get an API key, then call any path under your slug.

curl https://api.oanor.com/samplesize-api/SOME_PATH \
  -H "x-oanor-key: oanor_test_..."
const res = await fetch("https://api.oanor.com/samplesize-api/SOME_PATH", {
  headers: { "x-oanor-key": "oanor_test_..." }
});
const data = await res.json();
$ch = curl_init("https://api.oanor.com/samplesize-api/SOME_PATH");
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_HTTPHEADER, ["x-oanor-key: oanor_test_..."]);
$response = curl_exec($ch);
import requests
r = requests.get(
    "https://api.oanor.com/samplesize-api/SOME_PATH",
    headers={"x-oanor-key": "oanor_test_..."},
)
print(r.json())

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