I haven't yet read the new Nall report, but I did notice that it is based
upon estimated number of hours flown, per the FAA. No one (here) seems to
question or even want to see the assumptions on the number of hours flown.
Do you know how this number is estimated?

What is curious to me is that when I previously posted the data (from BTS)
about aviation subsidies (by sector)based on hours flown, many people
howled that no one could possibly know how many GA hours are actually
flown. They used that to dismiss the idea that GA is heavily subsidized.
But the Nall study is accepted as science.

I don't know how the number is estimated, but in your two examples the
number is being used in two different ways, and that's an important
difference. In the case of the Nall report (which I have not read), the
item in question is a trend or cluster (or lack thereof). The necessary
key assumption about GA hours is that there be consistancy across the
data sample being used. Systematic error in the number is not anywhere
near as important, since the trends would still show (or not).
Systematic error would tend to cancel out, while random error would not.
(Indeed, random error is what causes the illusion of clusters).

In the case of subsidies, the =actual= number is important. We are not
looking at trends, but rather, whether a certain value is (or is not)
greater than zero. To that end, random error would tend to cancel out,
and systematic error would propagate.

(For those unfamiliar with the terms, systematic error is an error
introduced by a deficiency in the method of measurement (for example,
using a ruler that is too short). It will be the same error every time
you do a measurement. Random error is an error introduced by the slop
in the measurement (for example, using a ruler that changes size with
temperature, and measuring on several different days). This error will
tend to be different for each measurement. It is similar to the
difference between "accuracy" and "precision".)

Jose
--
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