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For example, each of the three populations {0, 0, 14, 14}, {0, 6, 8, 14} and {6, 6, 8, 8} has a mean of 7. Their standard deviations are 7, 5, and 1, respectively. The third population has a much smaller standard deviation than the other two because its values are all close to 7.
Rule 30 has also been used as a random number generator in Mathematica, [3] and has also been proposed as a possible stream cipher for use in cryptography. [4] [5] Rule 30 is so named because 30 is the smallest Wolfram code which describes its rule set (as described below). The mirror image, complement, and mirror complement of Rule 30 have ...
Pro Evolution Soccer 2017 (officially abbreviated as PES 2017, also known in some Asian countries as Winning Eleven 2017) is a sports video game developed by PES Productions and published by Konami for Microsoft Windows, PlayStation 3, PlayStation 4, Xbox 360, Xbox One, Android and iOS.
Pro Evolution Soccer, often abbreviated as PES and also known as World Soccer: Winning Eleven 5 (Japanese: ワールドサッカー: ウイニングイレブン 5, Hepburn: Wārudosakkā: Uininguirebun 5) in Japan, [1] is a football sports simulation video game released in 2001.
Wichmann–Hill is a pseudorandom number generator proposed in 1982 by Brian Wichmann and David Hill. [1] It consists of three linear congruential generators with different prime moduli, each of which is used to produce a uniformly distributed number between 0 and 1. These are summed, modulo 1, to produce the result. [2]
The magic number for Team A to win the division is still "5": 58 + 8 − 62 + 1 = 5. As you can see, the magic number is the same whether calculating it based on potential wins of the leader or potential losses of the trailing team. Indeed, mathematical proofs will show that the three formulas presented here are mathematically equivalent.
In some cases, data reveals an obvious non-random pattern, as with so-called "runs in the data" (such as expecting random 0–9 but finding "4 3 2 1 0 4 3 2 1..." and rarely going above 4). If a selected set of data fails the tests, then parameters can be changed or other randomized data can be used which does pass the tests for randomness.
It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...