Chernoff Bounds
If the random variables may also be assumed to be independent, it is possible to obtain sharper bounds. Let δ > 0. Then
With this inequality it can be shown that
where μ is the mean of the distribution. Further discussion may be found in the article on Chernoff bounds
Read more about this topic: Chebyshev's Inequality
Famous quotes containing the word bounds:
“Great Wits are sure to Madness near alli’d
And thin Partitions do their Bounds divide;
Else, why should he, with Wealth and Honour blest,
Refuse his Age the needful hours of Rest?”
—John Dryden (1631–1700)