Calculators & Converters

Probability Calculator

Choose the probability model that matches your question: count favorable outcomes in an equally likely sample space, combine two independent events, or calculate a binomial success count over repeated trials. The result states the assumptions with its numerical probabilities.

Free online tool

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Assumes independent success/failure trials with the same p each time. Use 0 ≤ k ≤ n ≤ 1000; enter p from 0 to 1. Extremely small results may round to zero in floating-point arithmetic.

Calculations run locally in your browser. This tool does not upload the numbers you enter.

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How to use the Probability Calculator

  1. 01

    Select the model before entering values. Use counts for equally likely outcomes or decimal probabilities from 0 to 1 for the other models.

  2. 02

    For a binomial calculation, enter total trials n, target successes k, and the constant probability p of success on one trial.

  3. 03

    Calculate and review exact-count, inclusive-tail, or combined-event probabilities as appropriate. Copy or download the report.

Examples

A fair die

In the equally likely model, 1 favorable face out of 6 gives probability 1/6, or about 16.6667%. This ratio assumes all six faces have the same chance.

Three heads in ten flips

With n = 10, k = 3, and p = 0.5, the binomial probability of exactly three successes is 0.1171875. The at-most-three probability is 0.171875.

A count ratio needs equal likelihood

Dividing favorable outcomes by total outcomes works when the individual outcomes are equally likely. It does not model a weighted spinner merely by counting its colored regions. The complement is one minus the event probability.

Combining independent events

For independent A and B, the joint probability is P(A)P(B). The inclusive union adds both individual probabilities and subtracts the overlap. Exactly one includes A without B and B without A. Independent does not mean mutually exclusive: two independent events can occur together.

The binomial model

A binomial count assumes a fixed number of independent trials, two possible outcomes on each trial, and the same success probability every time. Exactly k successes uses a binomial coefficient times p^k(1 − p)^(n − k). The two tails include k itself. Probabilities are accumulated numerically; extremely small values can underflow to zero.

What to know

  • Binomial trials are capped at 1000. Counts in the equally likely model are capped at 1e12.
  • Probability output is numerical, rounded for display, and assumes the selected model is appropriate.

Common questions

Should I enter 25 or 0.25 for 25%?

Enter 0.25. Probability fields accept values from 0 through 1 rather than whole percentages.

Can I use this for dependent events?

The two-event model assumes independence. If one event changes the likelihood of the other, provide a suitable conditional model elsewhere instead of using the independent-event product.

Does at least k include k?

Yes. At least means X ≥ k, while at most means X ≤ k. Both cumulative answers include the exact-k outcome.

Can n or k be zero?

Yes. The binomial model allows 0 ≤ k ≤ n ≤ 1000. With zero trials, zero successes has probability one.

Sources & references