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This lecture covers the concept of moments in a distribution, including the raw moments, centered moments, and factorial moments. It explains how moments like expectation and variance are crucial in measuring the location and spread of a distribution, analogous to the center of gravity and moment of inertia in mechanics. The lecture also presents theorems related to moments, such as calculating the variance of a Poisson random variable. Practical examples and calculations are provided to illustrate the concepts discussed.