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Cantor's diagonal argument (among various similar names [ note 1]) is a mathematical proof that there are infinite sets which cannot be put into one-to-one correspondence with the infinite set of natural numbers – informally, that there are sets which in some sense contain more elements than there are positive integers.
Without proper rendering support, you may see question marks, boxes, or other symbols. In mathematical set theory, Cantor's theorem is a fundamental result which states that, for any set , the set of all subsets of known as the power set of has a strictly greater cardinality than itself. For finite sets, Cantor's theorem can be seen to be true ...
Dirichlet's theorem states that asymptotically, 25% of all primes end in each of these four digits. However, empirical evidence shows that the number of primes that end in 3 or 7 less than n tends to be slightly bigger than the number of primes that end in 1 or 9 less than n (a generation of the Chebyshev's bias). [34]
A prime number is a natural number greater than 1 with no divisors other than 1 and itself. According to Euclid's theorem there are infinitely many prime numbers, so there is no largest prime. Many of the largest known primes are Mersenne primes , numbers that are one less than a power of two, because they can utilize a specialized primality ...
Bessel's correction. In statistics, Bessel's correction is the use of n − 1 instead of n in the formula for the sample variance and sample standard deviation, [ 1] where n is the number of observations in a sample. This method corrects the bias in the estimation of the population variance. It also partially corrects the bias in the estimation ...
In particular, multiplying or adding two integers may result in a value that is unexpectedly small, and subtracting from a small integer may cause a wrap to a large positive value (for example, 8-bit integer addition 255 + 2 results in 1, which is 257 mod 2 8, and similarly subtraction 0 − 1 results in 255, a two's complement representation ...
The precise size that can be guaranteed is not known, but the best bounds known on its size involve binary logarithms. In particular, all graphs have a clique or independent set of size at least 1 / 2 log 2 n (1 − o(1)) and almost all graphs do not have a clique or independent set of size larger than 2 log 2 n (1 + o(1)). [32]
In the case of large integers, the best asymptotic complexity is (() ), with () the cost of -bit multiplication; this is near-linear and vastly smaller than the binary GCD algorithm's (), though concrete implementations only outperform older algorithms for numbers larger than about 64 kilobits (i.e. greater than 8×10 19265).