This is the probability of an event given (or conditional upon) the occurrence of another event, e.g. the probability of disease Y given exposure to factor X.
The probability, written Pr(A|B), of event A given that event B has occurred.
Conditional probability is the probability of an event occurring given that another event also occurs. It is expressed as P(A/B). It reads "Probability of Event A on condition of Event B." P(A/B) = P(A and B)/P(B), where P(B) is the probability of event B and P(A and B) is the joint probability of A and B.
A conditional probability is the probability of one event occurring given that another event has already occurred. For instance, if we are rolling two dice, the probability that their sum will be grater than seven is 11/36 (since of the 36 possible rolls, 11 are eight or greater), however the conditional probability that their sum will be greater than seven given that the first die rolled is a 4 is 2/6 or 1/2 (since we must roll a five or a six). [ DMTA p. 295, Ross,An Introduction to Probability
Likelihood of an event occurring given that a specific condition holds. EX: If two of ten restorations with Material X are observed and six of ten restorations with Material Y are observed, the probability of a failure (not conditional) is .40 – (2 + 6) / 20. The conditional probability of a restoration using Material X is .20 (2 / 10). Written p (F | X), probability of failure given condition X. [See also probability
the probability that an event will occur given that oneor more other events have occurred
The probability assigned to an event assuming that another event (called the conditioning event, or condition) has already happened.
the probability that a given event occurs, assuming that another event has occurred. Conditional Probability Coefficient: a similarity measure based on conditional probability.
The probability that one event will occur given that some other event has occurred.
The probability of an event, contingent on the occurrence of another event.
The chance that an event will occur that depends on the occurrence of a different event.
The probability of a proposition, A, being true given that all we know is some evidence, B. This is expressed as P(A | B).
the probability that an event will occur given that another event has already occurred.
The Likelihood of some Event given the prior occurrence of some other Event.
The probability that one event is true, given that another event is true. See: Bayes' Theorem.
The probability of some event (A) given that some other event (B) has occurred. Written P(A|B) and read "probability of A given B. Conditional probability is shown by the rectangular charts in the Evidence Visualizer's left-hand window, which show the relative probability of each attribute value given (conditioned on) each label value. Conditional probability can be thought of as evidence for a given label value.
The probability of an event, assuming that some other event has already occurred.
Observations or tests which can be used to modify prior probabilities using Bayesian calculation in risk estimations.
This article defines some terms which characterize probability distributions of two or more variables.