Chebyshev's Inequality is a statistical theorem that provides a bound on the probability that a random variable deviates from its mean by more than a specified number of standard deviations. This inequality is essential in probability theory as it applies to any distribution, regardless of its shape, making it a crucial tool in the analysis of variance and expectation. It highlights how much of the data will fall within certain bounds, enabling better understanding of dispersion in statistical data.
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