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This lecture covers the concept of conditional probability distributions, where the function fx(x | B) is defined as the probability of X = x given event B. The lecture also introduces the conditional expected value and provides an example of calculating the conditional PMFs of X ~ Geom(p) given X > n and X ≤ n.