Binomial Distribution

Statistics & Probability

Calculate exact Binomial probability mass P(X = k), cumulative probability P(X ≤ k), mean, and variance for n independent Bernoulli trials with success probability p.

Calculated Result
P(X = 10) = 0.1762

P(X ≤ 10) = 0.5881 · P(X ≥ 10) = 0.5881

Expected value μ
10
Variance σ²
5
Formula: P(X=k) = C(n,k) pᵏ (1−p)ⁿ⁻ᵏ

About this calculator

The Binomial distribution models discrete experiments with a fixed number of independent trials (n), where each trial has only two outcomes (success or failure) and a constant probability of success (p).

This calculator evaluates exact probabilities P(X = k), cumulative probabilities P(X ≤ k) and P(X ≥ k), and graphs the probability mass distribution alongside expected mean (μ = np) and standard deviation (σ = √(np(1-p))).

How It Works & Formula

FormulaP(X=k) = C(n,k) pᵏ (1−p)ⁿ⁻ᵏ

P(X = k) = C(n, k) × pᵏ × (1 - p)ⁿ⁻ᵏ, where C(n, k) = n! / (k!(n - k)!) is the binomial combination coefficient evaluated using log-gamma functions for large n.