Conditional probability and independence
Conditioning restricts attention to an event of positive probability.
Key knowledge
For P(B)>0, the conditional probability of A given B is P(A∩B)/P(B). Events A and B are independent when P(A∩B)=P(A)P(B).
Values and equations
P(A|B) = P(A∩B)/P(B)
- A, B
- Events with P(B)>0
- P(A|B)
- Probability of A conditional on B
Conditions and scope
- A and B belong to the same probability space.
- The event-ratio definition is undefined when P(B)=0; conditioning on continuous values requires a different construction.
- Independence is a mathematical property of a model and is not synonymous with disjointness.
Sources · 2
References
Sources retain their recorded scope. A source link alone does not establish verification of every statement.
Evidence and review
Conditional event probability and two-event independence.
2026-10-10 · Checked denominator condition and independence formula.
Foundational review
2026-10-10 · Fresh primary-source inspection of the complete compact record, including every statement, equation, quantity and material condition, followed by independent AI editorial review. This check does not certify all linked lessons or every passage of every cited publication.
Sources from other places
Agreement within this scope
Positive-probability event conditioning and product-form independence.
This event ratio does not define conditioning on a zero-probability continuous value.
University of Cambridge, Statistical Laboratory
- Probability · Axioms, conditioning and expectation United KingdomEnglish
§5.2 p.19; §6.1 p.22 (PDF p.29)
- Probability · Axioms, conditioning and expectation
Entry details
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- math-conditional-probability
- Revision
- core.1
- Structured reference record
- Essential core · first collection