Lucas Wells wrote:
> So, what I often see, then is:
>
> Orders (note: presented as Aug, Sep, Oct):
>
> Orders Issue: 10000, 9000, 9500
> Orders With Errors: 2000, 2500, 2250
> % Orders With Errors: 20%, 27.78%, 23.68%
>
> Fields With Errors:
>
> Name Field: 750, 1000, 1100
> Address Field: 750, 900, 700
> Products Ordered: 500, 550, 450
>
> % Fields With Errors (ie Number of Field Errors Divided By Total
> Errors for that month)
>
> Name Field: 37.50%, 40%, 48.89%
> Address Field: 37.50%, 38%, 31.11%
> Products Ordered: 25%, 22%, 20%
>
> Now, here's what makes me uneasy -- usually where I see a table
> containing percentages of a total over a period of time, as in '%
> Fields With Errors' straight above, I will also see a graph with all
> three data elements plotted (ie Name Field, Address Field, Products
> Ordered) across the period examined (ie Aug, Sep, Oct) with some
> commentary like:
>
> "We can see from Sep to Oct that the percentage of errors in the Name
> Field increased, however we managed to decrease the percentage of
> errors in the Products Ordered field."
>
> Now, I look at these percentages and I think to myself, 'They're
> percentages of a whole. If one goes up, then another must fall. It
> doesn't seem to make sense to examine them as if they are measures
> that can be seperately influenced (ie, as if we could decrease
> percentages across the board).'
You are absolutely correct, this is what happens when the innumerate
are let loose with computers. It reminds me a bit of the thing that was
circulating on the Net a while ago in which the birth year, year of
taking office, years in office at the end of WWII, and age at the end of
WWII were added up for each of Churchill, Mussolini, Hitler, Stalin, and
FDR and - surprise! - all five sums were the same.
(Diddy, diddy, diddy, diddy...)
-Robert Dawson
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