Dependent trials refer to a series of experiments or events where the outcome of one trial affects the outcome of subsequent trials. In this context, the probability of an event occurring in later trials is influenced by the results of earlier trials. For example, drawing cards from a deck without replacement is a classic case of dependent trials, as the composition of the deck changes with each draw. In contrast to independent trials, where each event's outcome is unaffected by previous events, dependent trials require careful consideration of how prior results impact future probabilities. Understanding this concept is crucial in fields like statistics and probability theory, where accurate predictions depend on recognizing these relationships.