I'm no statistician, but my gut reaction is that you're
probably comparing apples and oranges, so any comparison you
come up with is not likely to be very useful. As you suggest,
data distribution will play a large factor here.
In my earlier post, I meant to use the word "normalization" in
a more generic sense: instead of simply scaling the numbers
so they fit into a predictable range of values, you need to
convert all values to "universal units" which can be compared
directly. Depending on your attributes, this could be
quite complex: comparing a weight versus a height doesn't necessarily
make sense, as you observed. Those "universal units" might not be inches
or pounds; they might be "deviation from average" or
something else which is unit-independant.
But the problem will still be easier if you can separate this data
conversion step from the other parts of the process.
As far as getting "the right answer," I think you'd have better luck
asking someone with a high level of Statistics skill.
Alan.
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