Additivity of moments refers to the principle that the moments of a random variable can be calculated by summing the moments of its independent components. This principle is essential for understanding how different random variables contribute to the overall behavior of a system, particularly in terms of their mean and higher-order moments, such as variance and skewness. It plays a significant role in assessing the characteristics of distributions and allows for simplification in calculations involving multiple random variables.
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