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🎲 The Poisson Distribution for Counting Rare Events

Watch random rare events arrive over time and pile up into a live 3D histogram that converges on the theoretical Poisson curve as you tune the average rate.

AI & Machine Learning3DAdvanced60 FPS

Rare, independent events fall from the sky at random moments and fly into a live 3D histogram — watch it converge on the theoretical Poisson curve as more intervals are simulated.

🔬 What It Demonstrates

Each interval, the number of arriving events is drawn from a true Poisson process with rate λ. The solid bars track the observed frequency of each count; the wireframe bars show the exact theoretical probability P(k) = λᵏe⁻λ/k!.

🎮 How to Use

Set the average rate λ and simulation speed, pick an event context for flavour, and watch counts accumulate. Toggle the theoretical overlay off to see the raw sample histogram, and reset to start a fresh run.

💡 Did You Know?

For a genuine Poisson process the variance always equals the mean — watch the sample variance stat drift toward the same value as the sample mean as intervals accumulate.

⚙ Under the hood

Watch random rare events arrive over time and pile up into a live 3D histogram that converges on the theoretical Poisson curve as you tune the average rate.

probabilitydistributionrare eventsstatisticsmodelingdata analysisThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install