Conditional independence

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In probability theory, conditional independence describes situations in which an observation is irrelevant or redundant when evaluating the certainty of a hypothesis. It is the opposite of conditional dependence. Conditional independence is usually formulated in terms of conditional probability, as a special case where the probability of the hypothesis given the uninformative observation is equal to the probability without. If A {\displaystyle A} is the hypothesis, and B {\displaystyle B} and C {\displaystyle C} are observations, conditional independence can be stated as an equality: P ( A ∣ B , C ) = P ( A ∣ C ) {\displaystyle P(A\mid B,C)=P(A\mid C)} where P ( A...

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