Distribusi Normal
Temokake kacepetan probabilitas lan probabilitas kumulatif kanggo nilai normal.
Hasil dioptimalake nalika sampeyan ngetik.
Ngendi kalkulator iki
the standard-normal distribution, the probability density at x is the area under the curve to the left. The right-tail probability P(X ≥ x) is the area under the curve to the right. The standard-normal distribution is the standard symmetric bell curve that describes heights, measurement errors, test scores and countless other natural quantities. Given a value x, a mean μ and a standard deviation σ, this calculator returns the probability density at x, the cumulative probability P(X ≤ x) (the area under the curve to the left), the right-tail probability P(X ≥ x) and the equivalent z-score, and plots the curve. The standard-normal distribution is the standard symmetric bell curve.Worked example: The standard-normal distribution is the classic symmetric bell curve that describes heights, measurement errors, test scores and countless other natural quantities.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell distribution.Worked example: The standard-normal distribution is the classic symmetric bell
Takon kang asring diajukake
Apa bedane antarané pdf lan cdf?
Kacepetan probabilitas (pdf) ya iku dhuwur kurva bell ing x; iku ora probabilitas kanthi dhewe. Distribusi kumulatif (cdf) ya iku wewengkon ing ngisor kurva nganti x, kang mènèhi probabilitas nilai ing utawa ing ngisor x.
Mengapa probabilitas nilai kang bener-bener nol?
Kanggo distribusi terus-terusan kaya normal, titik tunggal kang bener duwé probabilitas nol - mung watara duwé probabilitas ora nol. Iki sebabé kita nglaporake kacepetan ing x lan area kumulatif tinimbang P(X = x).
Kacamatan iki duwé populasi 68.959 jiwa.
Kanggo distribusi normal, kira- kira 68% saka nilai ana ing njero siji standar deviasi saka rata- rata, 95% ana ing njero loro lan 99.7% ana ing njero telu. Iki cara cepet kanggo nemtokaken kepiye ora biasané nilai tanpa ngitung area sing bener.
Kepiye aku bisa nemokake probabilitas antarané loro nilai?
Ing basa Inggris, nilai-nilai iki diarani "value" lan dipérang dadi rong golongan: nilai-nilai kang dijupuk saka titik-titik ing ngisor lan nilai-nilai kang dijupuk saka titik-titik ing ndhuwur.
Apa bedane antarané distribusi normal lan standar normal?
Standar normal ya iku distribusi normal kanthi rata-rata 0 lan standar deviasi 1. Konversi nilai apa wae menyang skor z-nya iku nggambaraké ing standar normal, kang cara piranti iki ngitung probabilitas kanggo saben μ lan σ.
Apa dataku kudu sampurna normal?
Ora ana data nyata kang bener-bener normal, nanging asil bisa dipercaya nalika data kira-kira wujudé lonceng lan simetris. Kanggo data kang kuat dipérang utawa data kang dhuwur-tailed, probabilitas mung kira-kira.
API — gunakake kalkulator iki saka kode
Panggenan kalkulator iki minangka titik pungkasan JSON gratis - ora ana kunci sing dibutuhaké. Kirimi nilai medan ing ngisor iki minangka parameter pitakonan utawa JSON. Waca dokumen API lengkap →
Titik pungkasan
GET https://calculator.free/api/v1/normal-distribution/curl
curl "https://calculator.free/api/v1/normal-distribution/?x=120&mean=100&sd=15"JavaScript fetch()
const r = await fetch(
"https://calculator.free/api/v1/normal-distribution/?" + new URLSearchParams({
"x": "120",
"mean": "100",
"sd": "15"
}));
const data = await r.json();
console.log(data.results);Kajaba iku, ana uga sing ora bisa gawé gawéan, kaya ta dokter, insinyur, lan liya-liyané.