p(b|a) represents the conditional probability of event B occurring given that event A has already occurred. This concept is essential in probability theory as it allows us to update our beliefs about the likelihood of an event based on new information or evidence. Understanding p(b|a) helps in various applications, such as Bayesian inference, decision-making processes, and risk assessment.
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