Dependent events are occurrences in probability where the outcome of one event directly influences the outcome of another. This relationship means that the probability of one event changes when the other event is considered, leading to a need for conditional probability to accurately assess their joint likelihood. Understanding dependent events is crucial for applying Bayes' theorem, which helps in updating probabilities based on new information.
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