Birthday Problem (All Distinct)
Worked example: 23 people, 365 days → all distinct 0.4927 — press Try an example to run it live, then adjust anything.
Enter your known values, leave one input blank, and solves for the missing one. Tap a variable’s symbol to see what it means, with a typical value. Try different units for next level excitement!
Birthday Problem (All Distinct) explained
Line the picks up one at a time: the first is free, the second must dodge 1 used value out of N, the third must dodge 2, and so on, giving the product (N/N)((N−1)/N)((N−2)/N)… with n factors. With N = 365 days and n = 23 people, P(all birthdays distinct) ≈ 0.4927 — so the chance of a shared birthday is about 50.7%, the result Richard von Mises popularised in 1939 and which still startles people. Any World Cup squad of 23 is a coin flip for a shared birthday, and in practice about half of them have one.
The surprise dissolves once you count pairs rather than people: 23 people form 23 × 22/2 = 253 pairs, each with a 1/365 chance of matching. The classic trap is confusing this with "someone shares my birthday", which needs 253 other people to pass 50%. The same maths sets the cost of hash collisions — a 64-bit hash collides with even odds after only about 5 billion items, not 18 quintillion — a fact cryptographers call the birthday attack. Try three dice: n = 3, N = 6 gives (6 × 5 × 4)/6³ = 120/216 ≈ 0.556 for three different faces. Neither n nor N can be recovered in closed form, so this calculator solves for P.
Birthday Problem (All Distinct) formula
- = Probability all picks differ
- = Number of picks
- = Number of options
Missing one of these? Work it out first, then come back
- Probability all picks differ — Addition Rule (Mutually Exclusive Events), General Addition Rule
- Number of picks — Classical Probability, Binomial Distribution Mean
- Number of options — Classical Probability, Binomial Distribution Mean