Probability Calculator

Calculate single and multiple event probabilities with step-by-step solutions.

Single and combined eventsConditional probabilityUpdated May 2026

Outcomes that count as success.

All possible outcomes in the sample space.

Decimal · percent · fraction · odds

Probability result

30%

Basic probability

Complement

70%

Probability the event does not happen.

Decimal form

0.3

Fraction form

3/10

Odds in favor

3:7

Mode

Basic probability

Formula used

P(Event) = Favorable Outcomes ÷ Total Outcomes

3 ÷ 10

3 favorable outcomes out of 10 total outcomes gives a probability of 30%.
A probability of 0.3 means about 30% of similar trials.
The complement is 70%, meaning the event does not happen with that probability.
Choose the formula based on the event relationship.
Probability always depends on a clearly defined sample space.
Probability ranges from 0 to 1, where 0 means impossible and 1 means certain.

Probability Formulas and Rules

Basic Probability

P(Event) = Favorable Outcomes ÷ Total Outcomes

Complement

P(not A) = 1 − P(A)

Independent Events

P(A and B) = P(A) × P(B)

Union Rule

P(A or B) = P(A) + P(B) − P(A and B)

Conditional Probability

P(A | B) = P(A and B) ÷ P(B), when P(B) > 0

Mutually Exclusive Events

P(A or B) = P(A) + P(B)

Odds from Probability

Odds in favor = P(Event) ÷ P(not Event)

Variable Explanations

P(A)

Probability of event A.

P(B)

Probability of event B.

P(A and B)

Probability both events happen.

P(A or B)

Probability at least one event happens.

P(A | B)

Probability of A given B.

Complement

Probability an event does not happen.

Favorable outcomes

Outcomes that count as success.

Total outcomes

All possible outcomes in the sample space.

What Probability Means

Likelihood

Probability measures how likely an event is.

Range

Probability ranges from 0 to 1.

Impossible

0 means the event cannot happen.

Certain

1 means the event must happen.

Equally likely

0.5 means the event and its complement are equally likely.

Multiple forms

Probability can be written as a decimal, fraction, or percentage.

Worked Examples

Rolling a 6 on a fair die

Formula: P = favorable ÷ total

Substitution: 1 ÷ 6

Answer: 0.1667 = 16.67%

One face out of six is a 6.

Drawing a red card

Formula: P = favorable ÷ total

Substitution: 26 ÷ 52

Answer: 0.5 = 50%

Half the cards in a standard deck are red.

Complement probability

Formula: P(not A) = 1 − P(A)

Substitution: 1 − 0.30

Answer: 0.70 = 70%

If A has a 30% chance, not A has a 70% chance.

Coin flip and die roll

Formula: P(A and B) = P(A) × P(B)

Substitution: 0.5 × 1/6

Answer: 0.0833 = 8.33%

Independent events multiply.

Union probability

Formula: P(A or B) = P(A) + P(B) − P(A and B)

Substitution: 0.4 + 0.3 − 0.1

Answer: 0.6 = 60%

Subtract overlap once.

Conditional probability

Formula: P(A | B) = P(A and B) ÷ P(B)

Substitution: 0.12 ÷ 0.30

Answer: 0.4 = 40%

The sample space is limited to B.

Odds from probability

Formula: Odds = P ÷ (1 − P)

Substitution: 0.25 ÷ 0.75

Answer: 1:3

One success for every three failures.

Invalid setup

Formula: Favorable cannot exceed total

Substitution: 12 ÷ 10

Answer: Invalid

Favorable outcomes cannot be greater than total outcomes.

Independent, Dependent, and Conditional Probability

Independent

Events do not affect each other. Example: flipping a coin twice.

Dependent

Events affect each other. Example: drawing cards without replacement.

Conditional

Probability after new information is known. Example: P(A given B).

Probability Rules and Complements

Complement rule

P(not A) = 1 − P(A).

Union rule

Add probabilities and subtract overlap.

Intersection rule

For independent events, multiply probabilities.

Mutually exclusive

Events cannot happen at the same time.

Exhaustive outcomes

All possible outcomes together have probability 1.

Overlap

Overlapping events require subtracting the overlap once.

Common Use Cases

Games and dice
Card probability
Surveys and statistics
Risk estimates
Quality control
Forecasting basics
Simple science examples
Business metrics
Decision-making scenarios

Common Probability Mistakes

Using favorable outcomes greater than total outcomes.
Adding probabilities without subtracting overlap.
Multiplying probabilities for dependent events without adjusting.
Confusing probability with odds.
Treating 70% as 70 instead of 0.70.
Forgetting complement probability.
Using conditional probability when P(B) is zero.
Assuming unlikely means impossible.

Understanding Your Results

Probability result

Likelihood of the event.

Percent form

Probability out of 100.

Decimal form

Probability from 0 to 1.

Fraction form

Favorable share of the whole.

Complement

Probability the event does not happen.

Odds

Comparison of happening vs not happening.

Frequently Asked Questions