I-Calculator ye-Binomal Probability

Thola ingozi yempumelelo ye-k ezindaweni ezizimele ze-n.

%
P(X = k)
P(X ≤ k)
P(X ≥ k)
Isilinganiso (n·p)
Ukuhluka
Ukuhluka okujwayelekile

Iziphetho zivuselelwa uma ubhala.

Malunga nale khadi

the binomial distribution is used to calculate the number of successes in a fixed number of independent trials, each with the same success probability — the classic "how many heads in ten coin flips" problem. It returns the probability of exactly k successes, P(X = k) = C(n, k)·pᵏ·(1 − p)ⁿ⁻ᵏ), along with the cumulative probabilities of at most k and at least k successes. It also reports the distribution’s mean (n·p), variance (n·p·(1 − p)) and standard deviation, and shows the full probability distribution as a table and a chart.The binomial probability calculator uses the binomial distribution to model the number of successes in aWorked example:The term C(n, k) is the number of ways to choose which k of the n trials succeed, pᵏ is the chance those k succeed and (1 − p)ⁿ⁻ᵏ the chance the rest fail. The distribution’s mean (n·p) is 1.The term C(n, k) is the number of ways to choose which k of the n trials succeed, pᵏ is the chance those k succeed and (1 − p)ⁿ⁻ᵏ the chance the rest fail. The full probability distribution is shown as a table and a chart.The binomial probability calculator uses the binomial distribution to model the number of successes in a fixed number of independent trials, each with the same success probability — the classic "how many heads in ten coin flips" problem.Worked example:The term C(n, k) is the number of ways to choose which k of the n trials succeed, pᵏ is the chance those k succeed and (1 − p)ⁿ⁻ᵏ the chance the rest fail.The term C(n, k) is the number of ways to choose which k of the n trials succeed, pᵏ is the chance those k succeed and (1 − p)ⁿ⁻ᵏ the chance the rest fail.The term C(n, k) is the number of ways to choose which k of the n trials succeed, pᵏ is the

Imibuzo ebuzwa kaningi

Ngabe ngingakwazi ukusebenzisa ukusabalalisa kwe-binomial?

Sebenzisa uma kunenani eliqinile lemizamo ehlukile, yonke imizamo inemiphumela emibini kuphela (uphumelela noma ukungabi khona), futhi ingozi yokuthola imiphumela ifana ngaso sonke isikhathi - njenge-flipping coin 10 times or counting defective items in a batch.

Yini ushintsho phakathi kweP (X = k) ne P (X ≤ k)?

P(X = k) yithuba lempumelelo ye-k, ngenkathi P(X ≤ k) ihlanganisa ithemba le-0, 1, … kuze kube yi-k. Uhlobo oluphelele luphendula imibuzo njenge "yini ithemba lempumelelo ye-3?"

Yini i-"n choose k"?

C(n, k), funda "n khetha k", yinani lezindlela ezahlukene zokukhetha ukuthi yiziphi i-k ze-n ezizamayo eziphumelelayo. Ezizameni ezingu-10 neziphumelelayo ezingu-3 kukhona i-C(10, 3) = 120 ezinjalo, futhi ngayinye isiza ukukwazi okuphelele.

Yini isilinganiso kanye nesimo se-deviation se-binomial distribution?

Isilinganiso (izinga elilindelekile lokuphumelela) yi n·p futhi ushintsho yi n·p·(1 − p), ngakho ukuhluka okujwayelekile yi √(n·p·(1 − p)). Ukudlalwa kwemali efanele 10, silinganiso yi 5 futhi ukuhluka okujwayelekile kumalunga ne 1.58.

Ngabe ngizokwazi ukulinganisela i-binomial nge-distribution ejwayelekile?

Uma i-n ikhulu futhi zombili i-n·p ne-n·(1 − p) ziyi-10, i-binomial ifinyelelwa kahle ngokuhlukaniswa okujwayelekile ngesilinganiso esifanayo kanye ne-standard deviation. Le yisisekelo sezindlela eziningi zokuvavanya ukulingana kwesampula enkulu.

Ngiyithola kanjani ingozi yempumelelo encane k?

P(X ≥ k) iqoqa izimo ze k, k+1,... kuze kube n izimpumelelo. Kulingana 1 − P(X ≤ k − 1), futhi le calculator yezinto ezinomthelela omibili ikhombisa ngokuqondile ngakwesokudla "ngokuningi" inzuzo.

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Nquma le kalkuli njengendawo ephelezelwa i-JSON - akukho isitshixo esidingekayo. Thumela amaxabiso endawo ngezansi njengepharamitha yombuzo noma i-JSON. Funda i-API egcwele →

Ingxenye yendawo

GET https://calculator.free/api/v1/binomial-probability/

curl

curl "https://calculator.free/api/v1/binomial-probability/?n=10&k=3&p=50"

JavaScript fetch()

const r = await fetch(
  "https://calculator.free/api/v1/binomial-probability/?" + new URLSearchParams({
    "n": "10",
    "k": "3",
    "p": "50"
  }));
const data = await r.json();
console.log(data.results);

Izibalo ziyisilinganiso esisetshenziswa ukuqondisa kuphela, hhayi ukucebisa ngezimali, ukwelashwa noma ukukhokha.