Nhazi
Chọ̀ọ́ nha saịmpọn nke saịrịrị maka n'ógé nke mmehie.
Nhọrọ ndị ahụ ga-akpụzi mgbe ị na-etipụta.
N'ihe banyere calculator a
This sample size calculator finds how many people you need to survey for a chosen margin of error and confidence level — the planning step before you run a poll or study. It uses the standard formula n = z²·p(1 − p) / e², where z is the critical value for the confidence level, p the expected proportion and e the target margin of error as a decimal.
When you supply a total population size it also applies a finite-population correction, n = n₀ / (1 + (n₀ − 1)/N), which lowers the required sample when you are surveying a large fraction of a small group. A table shows the sample needed at several common margins of error, and the result is always rounded up because you cannot survey a fraction of a person.
Worked example: for a 5% margin at 95% confidence with an unknown proportion (p = 0.5), n = 1.96² × 0.5 × 0.5 ÷ 0.05² = 3.8416 × 0.25 ÷ 0.0025 ≈ 384.16, so you need 385 respondents. Tightening the margin to 3% pushes that to about 1,068. The default 50% proportion gives the largest, safest sample; entering a better estimate of the true proportion reduces it.
Ajụjụ ndị a na-ajụkarị
Olee otú e si etinye nha nlele ahụ?
The base formula is n = z²·p(1 − p) / e², where z is the confidence critical value, p the expected proportion and e the margin of error as a decimal. The result is rounded up because you cannot survey a fraction of a person.
Gịnị bụ ngbanwe nke ndị mmadụ?
Mgbe ọnụọgụgụ ndị mmadụ gị dị obere, ịchọrọ nzaghachi dị obere karịa ihe n'okpuru fomulụ na-ekwu. Nhazi n = n₀ / (1 + (n₀ − 1)/N) na-ewepụ saịmpọn ahụ n'ihu ọnụọgụgụ ndị mmadụ N. Ọ dị mkpa mgbe saịmpọn ahụ bụ akụkụ nke zuru ezu.
Olee ndị mmadụ m ga-achọ maka 95% nrụnye n'okpuru?
Ọ na-adabere na margin nke njehie ị nwere ike ịnabata. Na 95% nghọta na 5% margin na ọ dịghị tupu amụma ị chọrọ banyere 385 respondents; a 3% margin chọrọ banyere 1,068 na 1% margin banyere 9,604.
Gịnị mere ọbụla ọkara nke nha saịlọn ahụ ji akpụgharịa?
I gaghị enwe ike ịkpọọ akụkụ nke onye ahụ, yabụ ọbụla n'ime ihenhọrọ nke n'ime ọbụla bụ nke a na-akpụga n'elu n'imebi nke ọzọ. Akpụga n'elu n'ebe ọbụla n'ebe ọbụla na-eme ka ọbụla nke n'imebi ahụ dị obere karịa nke ịchọrọ.
M ga-ahapụ nha ndịna-ebubata ahụ na-enweghị ihe ọ bụla?
Wepụ ya na séèrò (maọbụ ọbụla) mgbe ọnụọgụgụ bụ nnukwu ma ọ bụ a naghị ama, nke na-enye ụkpụrụ "ọnụọgụgụ na-enweghị atụ" nha saịmpọn. Tinye ọnụọgụgụ ọbụla mgbe ọ bụ obere nke ọma ka ngbanwe ahụ na-abawanye ọnụọgụgụ.
Olee otú m ga-esi belata nha nlele ahụ chọrọ?
Accept a larger margin of error, use a lower confidence level, or supply a proportion further from 50% if you have a reliable estimate. Each of these lowers the number of responses the formula demands.
API — jiri kaadị a site na kóòdù
Kpọọ kalkulata a dịka ebe ngwụcha JSON n'efu - enweghị kii achọrọ. Ziga valiu ebe ahụ n'okpuru dịka paramita ajụjụ mọọbụ JSON. Ihe ọbụla ị na-ewepụ na-eji dìfọ́ọ̀ltụ̀ nke a na-edebe ihuakwụkwọ a na ya; parameter a na-amaghị bụ 400, ọ dịghị sẽọ̀rọ̀. Gụọ ngwe ndị ahụ niile →
Ebemkpofuozi
GET https://calculator.free/api/v1/sample-size/curl
curl "https://calculator.free/api/v1/sample-size/?conf=1.96&e=5"JavaScript fetch()
const r = await fetch(
"https://calculator.free/api/v1/sample-size/?" + new URLSearchParams({
"conf": "1.96",
"e": "5"
}));
const data = await r.json();
console.log(data.results);Ihe a na-ahụta bụ n'ihi nlekọta n'ozuzu ya, ọ bụghị nlekọta ego, ọgwụ ma ọ bụ nlekọta ego.