Home / Statistics Topics

Module 2 · Probability Foundations · Topic 7

Independence

Independent Events. Two events are independent if the occurrence of one does not change the probability of the other. Formally, A and B are independent if P(A | B) = P(A).

Open the interactive lessonAll topics

Key formulas

Testing Independence

A and B are independent if and only if P(A ∩ B) = P(A) × P(B)

From the Probability Foundations formula sheet

  • Conditional Probability: P(A | B) = P(A and B) / P(B) — Probability of A after restricting attention to cases where B occurred.
  • Bayes' Theorem: P(A | B) = P(B | A)P(A) / P(B) — Updates a prior probability after observing evidence.

See the full formula reference

Worked example

Worked Example

Roll a die and flip a coin. P(6 and heads) = P(6) × P(heads) = (1/6)(1/2) = 1/12. The die roll does not affect the coin flip, so they are independent.

When to use it

Independence vs Mutually Exclusive

Don’t confuse these! Mutually exclusive events cannot both happen. When both events have positive probability, they are dependent. Independent events can both happen - one just doesn’t influence the other.

Related glossary terms

  • Independence: Two events are independent when one occurring does not change the probability of the other. Example: Two separate fair coin flips are independent.

Browse the full glossary

Go interactive

Work this topic in StatRise

Start with the free descriptive-statistics module and daily practice; this module's tracked lesson unlocks with Premium.

Probability Foundations lesson (Premium)Probability calculatorsCombinatorics calculatorsCoin & Dice simulationPractice questions

Keep reading

More topics

Previous: Conditional ProbabilityNext: Bayes' TheoremAll statistics topics
CalculatorsLessonsPracticeGuidesTopicsPremiumRestore purchasePrivacyTerms

© 2026 StatRise. Statistics calculators, lessons, practice, and simulations — progress stays in your browser, no account required.

More study tools: CalcRef · Discretica · ScoreMint · PhysRef