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^{-x} \approx 1 - x$, we find $m \approx \sqrt{n}$. So if you have $n$ possible hash values, you have a 50% probability of one or more collisions after hashing $\sqrt{n}$ items. This estimate is …
answered Jan 1 '18 by Pseudonym
2
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For sufficiently large $M$, the size distribution of hash slots with good uniform hash functions follows a Poisson distribution. Let $\lambda = \frac{N}{M}$ be the load factor. Then the expected prop …
answered Nov 7 '16 by Pseudonym
2
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In addition to everything that others have said: any cipher is an invertible "hash" function. And there are standard ways to construct them; one common way of turning a one-way function into an invert …
answered Jan 28 '17 by Pseudonym
3
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The mean chain length is the sum of the chain lengths divided by the number of chains. The sum of the chain lengths is, by definition $n$ and the number of chains is $m$. This is by far the easiest wa …
answered Feb 16 '16 by Pseudonym