Sharpened Bounds
Chebyshev's inequality is important because of its applicability to any distribution. As a result of its generality it may not (and usually does not) provide as sharp a bound as alternative methods that can be used if the distribution of the random variable is known. To improve the sharpness of the bounds provided by Chebyshev's inequality a number of methods have been developed.
Read more about this topic: Chebyshev's Inequality
Famous quotes containing the word bounds:
“At bounds of boundless void.”
—Samuel Beckett (1906–1989)