Chebyshev's Inequality is a statistical theorem that provides a way to estimate the minimum proportion of observations that fall within a specified number of standard deviations from the mean, regardless of the distribution shape. This inequality is particularly useful for understanding the spread of data in continuous random variables, linking it to the concepts of expected value and variance by allowing for bounds on how far values can deviate from the mean.
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