Kalkulator Probabilitas Binomial
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Ngenai kalkulator iki
the binomial distribution, the probability of exactly k successes is equal to the probability of at least k successes. 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. 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. The binomial probability calculator uses the binomial distribution to model the number of successesTheWorked 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 probability of the success.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.The term C(n, k) is the probability of the success of the n trials.
Takon-takon kang kerep diajukake
Kapan aku bisa nggunakake distribusi binomial?
Digunakeun nalika aya jumlah anu teu bisa dirobah tina percobaan independen, unggal percobaan ngan ukur ngagaduhan dua hasil (kauntungan atanapi karugian), sareng kamungkinan kasuksésan anu sami unggal waktos - sapertos ngaleupaskeun koin 10 kali atanapi ngitung item anu cacad dina batches.
Apa bedane antara P(X = k) lan P(X ≤ k)?
P(X = k) ya iku kamungkinan saka persis k sukses, nalika P(X ≤ k) nambahake kamungkinan saka 0, 1,... nganti k sukses. Versi kumulatif mangsuli pitakon kaya "apa kamungkinan saka paling ora3sukses?"
Apa tegese "n milih k"?
C(n, k), dibaca "n pilih k", nyaéta jumlah cara béda pikeun milih k tina n usaha anu suksés. Pikeun 10 usaha sareng 3 suksés aya C(10, 3) = 120 kombinasi sapertos kitu, sareng unggal kontribusi kana probabilitas total.
Apa rata-rata lan standar deviasi saka distribusi binomial?
Rata-rata (jumlah suksés anu diharepkeun) nyaéta n·p sarta variasi nyaéta n·p·(1 − p), jadi standar deviasi nyaéta √(n·p·(1 − p)). Pikeun 10 kali lempar koin anu adil rata-ratana nyaéta 5 sarta standar deviasi sakitar 1.58.
Kapan aku bisa nganggep binomial kanthi distribusi normal?
Nalika n gedé sarta n·p jeung n·(1 − p) sahenteuna kira-kira 10, binomial bisa dikira-kira ku distribusi normal kalayan rata-rata jeung standar deviasi anu sami. Ieu mangrupa dasar tina loba uji proporsi sampel gedé.
Kepiye carane aku nemokake probabilitas paling ora k sukses?
P(X ≥ k) ngajumlahkeun kamungkinan k, k+1,... nepi ka n kali suksés. Éta sami sareng 1 − P(X ≤ k − 1), sareng kalkulator kamungkinan binomial ieu ngalaporkeun éta langsung di samping nilai "sahenteuna".
API — gunakake kalkulator iki saka kode
Ngadongékeun kalkulator ieu minangka titik akhir JSON bébas — teu peryogi kunci. Kirim nilai medan di handapeun minangka parameter pitakonan atawa JSON. Waca dokumen lengkap API →
Tampilan
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);
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