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My advice remains the same:
a) You really ought to test each hypothesis against some
sort of control. As the proverb says: When all else
fails, measure it. It doesn't pay to guess about whether
the probability is "exceedingly low" or not.
b) It is /sometimes/ possible to draw reliable statistical
inferences, but it requires better evidence than this.
Either there needs to be a more blatant screw-up, or we
need vastly more data.
To say the same thing another way: In this data, the
signal-to-noise ratio is really lousy. We need either
a bigger signal or less noise.
c) There's no such thing as a random number. You can have
a random /distribution/ over numbers, but then the randomness
is in the distribution, not in any particular number that
might have been drawn from the distribution.