확률
The Mathematics Of

Probability

확률 · 確率 · Probabilité

From ancient dice carved from bone to the algorithms that shape your feed — probability is the glamorous mathematics of uncertainty, draped in chrome and crystal.

0Faces On A Die
0Cards In A Deck
Possible Outcomes
02

The Gentleman's
Gamble

In 1654, Blaise Pascal and Pierre de Fermat exchanged letters that would birth probability theory — all because a gambler named Antoine Gombaud wanted to know when to bet on dice. Mathematics, born from the casino floor, dressed in lace and candlelight.

The Problem of Points
P(A) = favorable outcomestotal outcomes
P = 0.5 H T
“The theory of probability is at bottom nothing but common sense reduced to calculus.”
— Pierre-Simon Laplace
-3σ -2σ -1σ μ +1σ +2σ +3σ
03

The Bell Curve
Catwalk

The Gaussian distribution — mathematics' most glamorous curve. She appears everywhere: in heights, in stock returns, in measurement errors. 68% of all data falls within one standard deviation. She is the probability world's supermodel.

68.2%Within ±1σ
95.4%Within ±2σ
99.7%Within ±3σ
Move your cursor to reshape the distribution
04

Updating Your
Beliefs

Reverend Thomas Bayes gave us the ultimate flex: a mathematical framework for changing your mind. Prior knowledge meets new evidence, and out comes a posterior probability — more refined, more dangerous, more beautiful.

P(A|B) = P(B|A) · P(A)P(B)
Posterior
Likelihood
Prior
Evidence
0.50
0.80
05

The Algorithm
Age

Today, probability drives everything — from your Netflix recommendations to self-driving cars. Machine learning is probability theory wearing designer sneakers and a hoodie. Every neural network is a probability machine, computing likelihoods at the speed of silicon.

Monte Carlo MethodsRandom sampling as computational power
Markov ChainsMemoryless probability transitions
Deep LearningBillions of probabilistic weights