Chebyshev's inequality

Chebyshev's Inequality is a statistical rule that tells us how much of the data in a distribution is likely to be close to the average. It states that no more than 1/k² of the data points can be more than k standard deviations away from the mean, for any k greater than 1. This means, for example, if k=2, at least 75% of the data will fall within two standard deviations of the average. The inequality is useful because it applies to all distributions, regardless of their shape, helping to understand data variability and reliability.