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experimental evidence says that it is in fact a uniform distribution:

  r = random.Random()

  def one_to_five():
    return r.randint(1, 5)

  def mod_seven():
    return (sum(one_to_five() for x in xrange(7)) % 7) + 1

  def test_dist(lst):
    return [(x, lst.count(x)) for x in [1,2,3,4,5,6,7]]



i've tried it out experimentally in google docs and it looks really good for big numbers. No real proof tho and it might be that the errors counter each other by chance:

http://spreadsheets.google.com/ccc?key=pq4tB7LQWN03gF7ImGhIP...


Have a look at the distributions for each sum here: http://brianpmearns.com/ext/dice/dice.html

edit: Oops bad addition on my part, could be uniform, but you'd have to work out the actual number exactly.


here are the exact numbers:

1 -> 11177

2 -> 11172

3 -> 11158

4 -> 11144

5 -> 11144

6 -> 11158

7 -> 11172

...not quite


I've done a lot of Python but never knew about xrange - thanks!




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