The Lindeberg-Lévy Theorem is a fundamental result in probability theory that provides conditions under which the sum of a sequence of independent random variables will converge in distribution to a normal distribution. This theorem serves as a key extension of the Central Limit Theorem, particularly by specifying a condition—known as the Lindeberg condition—that ensures the convergence applies even when the random variables do not have identical distributions.
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