Divide favorable outcomes by possible outcomes. Rolling a die, the chance of a 4 is 1 ÷ 6 ≈ 0.167 = 16.7%.
Carregando ferramenta… / Loading tool…
Probability of an event and combinations of two events.
The classical probability of an event is the ratio of favorable outcomes to possible outcomes (assuming equally likely results), a number always between 0 and 1, or between 0% and 100%. In one-event mode the tool computes P(A) = favorable ÷ possible, the complement P(not A) = 1 − P(A) and the chance as a favorable:unfavorable ratio. In two-event mode it combines P(A) and P(B): the intersection P(A∩B), assuming independence (P(A)·P(B)) when you don't provide it, the union P(A∪B) = P(A) + P(B) − P(A∩B), the probability of at least one occurring, the conditional P(A|B) = P(A∩B) ÷ P(B) and the complements. Probabilities can be typed as a decimal (0.5) or a percentage (50%): values greater than 1 or carrying a % symbol are converted automatically. Every result comes with the steps, and everything runs locally in your browser.
The foundation is the classical definition: P(A) = number of favorable outcomes ÷ number of possible outcomes, valid when all outcomes are equally likely. From that number come the complement P(not A) = 1 − P(A) and the odds ratio, which compares favorable to unfavorable cases (for example, 1:5).
With two events, four formulas do the heavy lifting. The intersection P(A∩B) is the chance both occur, if the events are independent, it equals P(A)·P(B). The union P(A∪B) = P(A) + P(B) − P(A∩B) avoids double-counting the overlap. The conditional P(A|B) = P(A∩B) ÷ P(B) readjusts the chance of A given that B occurred.
Example 1, one event: rolling an even number on a die. There are 3 favorable outcomes (2, 4, 6) out of 6 possible, so P = 3 ÷ 6 = 0.5 = 50%. The complement is P(not even) = 1 − 0.5 = 0.5, and the odds ratio is 3:3, which simplifies to 1:1.
Example 2, two independent events: a coin lands heads (P = 0.5) and a die shows a 6 (P = 1 ÷ 6 ≈ 0.1667). Without an intersection, the tool assumes independence: P(A∩B) = 0.5 × 0.1667 ≈ 0.0833. The union is 0.5 + 0.1667 − 0.0833 ≈ 0.5833, i.e. a ~58.3% chance of at least one occurring.
Mind the input: a number between 1 and 100 without a % symbol is read as a percentage (30 becomes 0.30), so for a probability of 0.3 type either 0.3 or 30%. Leaving the intersection blank makes the tool assume independence; for mutually exclusive events (which cannot occur together), enter P(A∩B) = 0. And remember the intersection can never exceed the smaller of the two probabilities: P(A∩B) ≤ min(P(A), P(B)).
In practice, these computations show up in games and betting, quality control (chance of at least one defective part), reliability of redundant systems, medical testing (where conditional probability is the basis of Bayes' theorem) and risk estimates. The classical definition assumes equally likely outcomes, for loaded dice or observed frequencies, use empirical probabilities.
Paste the code into your HTML and the tool shows up on your page, without J-Kit's navigation and ads. It still runs in the browser of whoever visits your site.
<iframe
src="https://jkit.tools/embed/en-US/probability-calculator"
width="100%"
height="600"
style="border:0"
loading="lazy"
title="Probability Calculator"
></iframe>These references help contextualize formulas, standards, APIs and limitations used on this page. They do not replace professional validation when a result has legal, financial, medical or operational impact.
Divide favorable outcomes by possible outcomes. Rolling a die, the chance of a 4 is 1 ÷ 6 ≈ 0.167 = 16.7%.
Calculations run in your browser. No data is sent to a server.