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Markov's and Chebyshev's Inequalities Explained

104 pointsby foobalmost 8 years ago

2 comments

beagle3almost 8 years ago
This Chebychev&#x27;s inequality (there are several) is a simple extension of Markov (by setting phi(x) = |x|^2 - see the Wikipedia article on Markov&#x27;s inequality).<p>There is another simple extension[0], much less known, of setting phi(x) = exp(-s*x), and taking the infimum over all s; it is often tractable and yields much, much sharper bounds.<p>[0] <a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Chernoff_bound" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Chernoff_bound</a>
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cscheidalmost 8 years ago
If you have a hard time remembering exactly how Markov inequality goes (like I do), there&#x27;s a great mnemonic from which you can construct the general version:<p>- if the average person is 6&#x27; tall, than at most 10% of the people are taller than 60&#x27;.
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