This isn’t an even smearing, but looking at a random piece of text and converting the letters into 1-26 should be sufficient for many purposes. If you want additional randomness, add the letters of the first nontrivial word up mod 26(or mod 10, or whatever).
No, that won’t work due to Benford’s Law. In this case, there will be a lot more 1′s and somewhat more 2′s than the other 8 digits. I.e. 10 letters have numbers beginning with 1 and 7 have numbers beginning with 2, but none have letters beginning with 0. The non-random distribution of letters in English text will probably also skew your results.
Hence why I said “sufficient for many purposes”. If you’re trying to choose between 3 places to eat lunch, for example, “the next letter of text mod 3″ is a perfectly acceptable method for determining it. If you’re trying to encrypt nuclear launch codes, not so much.
Benford’s Law applies to the first digit, whereas Alsadius’s use of modulo means taking the last one, which would be much less biased (the bias would be drowned by the bias from common words and letters).
This isn’t an even smearing, but looking at a random piece of text and converting the letters into 1-26 should be sufficient for many purposes. If you want additional randomness, add the letters of the first nontrivial word up mod 26(or mod 10, or whatever).
No, that won’t work due to Benford’s Law. In this case, there will be a lot more 1′s and somewhat more 2′s than the other 8 digits. I.e. 10 letters have numbers beginning with 1 and 7 have numbers beginning with 2, but none have letters beginning with 0. The non-random distribution of letters in English text will probably also skew your results.
Hence why I said “sufficient for many purposes”. If you’re trying to choose between 3 places to eat lunch, for example, “the next letter of text mod 3″ is a perfectly acceptable method for determining it. If you’re trying to encrypt nuclear launch codes, not so much.
Benford’s Law applies to the first digit, whereas Alsadius’s use of modulo means taking the last one, which would be much less biased (the bias would be drowned by the bias from common words and letters).