Probability Calculator
This probability calculator handles the two questions people ask most. With two independent events, it gives the chance that both happen, that at least one happens, that exactly one happens, that neither happens and that A doesn't happen. With repeated trials, it uses the binomial distribution to find the chance of exactly, at most or at least k successes in n tries, plus the chance of at least one success and the expected count.
Updated
Results
- P(A or B): at least one happensTwo-events mode
- Exactly one happensTwo-events mode
- Neither happensTwo-events mode
- P(not A)Two-events mode
- P(X ≤ k): at most k successesRepeated-trials mode
- P(X ≥ k): at least k successesRepeated-trials mode
- At least one successRepeated-trials mode: 1 − (1 − p)ⁿ
- Expected number of successesRepeated-trials mode: n × p
Results are estimates. See the methodology below.
How to use the probability calculator
- Choose a mode. Pick two independent events to combine two probabilities, or repeated trials for the same event tried several times.
- Enter probabilities as percentages from 0 to 100. A fair coin is 50; rolling a six on one die is 16.67.
- For repeated trials, enter the number of trials n (1 to 1,000) and the number of successes k you're asking about. k can't be greater than n.
- Read the results. Two-event mode shows P(A and B), P(A or B), exactly one, neither and not A. Repeated-trials mode shows exactly k, at most k, at least k, at least one and the expected number of successes.
Formulas and assumptions
Both modes assume independence: the outcome of one event doesn't change the probability of the other. Coin flips, dice rolls and draws with replacement are independent; drawing cards without putting them back is not.
Two independent events
- Both:
P(A and B) = P(A) × P(B) - At least one:
P(A or B) = P(A) + P(B) − P(A) × P(B) - Exactly one:
P(A) + P(B) − 2 × P(A) × P(B) - Neither:
(1 − P(A)) × (1 − P(B)) - Not A:
1 − P(A)
Repeated trials (binomial distribution)
For n independent trials, each with success probability p, the chance of exactly k successes is:
P(X = k) = C(n, k) × pᵏ × (1 − p)ⁿ⁻ᵏ
where C(n, k) is the number of ways to choose k trials out of n. P(X ≤ k) adds up the terms from 0 to k, and P(X ≥ k) is 1 − P(X ≤ k) + P(X = k). The chance of at least one success is 1 − (1 − p)ⁿ, and the expected number of successes is n × p. The calculator works with logarithms of factorials, so large n stays accurate.
Examples
1. Two backup drives
Suppose each of two drives has a 3% chance of failing in a given year, independently of the other. The chance that both fail is 0.09%, the chance that at least one fails is 5.91% and the chance that neither fails is 94.09%. A second drive turns a 3% risk of losing everything into less than one in a thousand.
2. Sixes in ten rolls
Roll a fair die 10 times (p = 16.67%, n = 10, k = 2):
| Question | Probability |
|---|---|
| Exactly 2 sixes | 29.07% |
| At most 2 sixes | 77.51% |
| At least 2 sixes | 51.56% |
| At least one six | 83.86% |
| Expected number of sixes | 1.67 |
3. Free throws
A 75% free-throw shooter takes 10 shots. The chance of making exactly 8 is 28.16%, and the chance of making at least 8 is 52.56%. On average the shooter makes 7.5. For just two shots, two-event mode gives 56.25% for both, 37.5% for exactly one and 6.25% for missing both.
Reading the results
A probability is a long-run frequency, not a promise. A 29% chance of exactly two sixes means that in many sets of 10 rolls, roughly 29 out of 100 sets end that way. Over a single set, anything can happen.
Check the independence assumption before relying on the numbers. Weather on consecutive days, a team's games in a slump or parts from the same faulty batch tend to be linked, and multiplying their probabilities will understate how often bad outcomes cluster together.
Frequently asked questions
What's the difference between "A or B" and "exactly one"?
"A or B" counts every case where at least one event happens, including both. "Exactly one" excludes the case where both happen. That is why P(A or B) is always at least as large as P(exactly one).
How do I calculate the probability of at least one success?
Find the chance of no successes and subtract it from 1: 1 − (1 − p)ⁿ. For three rolls of a die, that is 1 − (5/6)³, about 42%. Repeated-trials mode shows it directly.
Can I use this for dependent events?
No. If one event changes the odds of the other, you need conditional probability: P(A and B) = P(A) × P(B given A). Drawing two aces from a deck without replacement is a typical dependent case.
Why do I need to enter percentages?
Percentages are easier to read for most people. If you have a probability as a decimal, multiply by 100: 0.25 becomes 25. For a fraction such as 1/6, divide first: 16.67.
Why do I get an error for k?
You can't have more successes than trials, so k must be a whole number between 0 and n.
Sources
Results assume independent events with the probabilities you enter and are provided for general information. They don't predict any single outcome and are not betting or financial advice.