On 10/7/13 6:03 AM, Tim Shoppa wrote:
Proposing a random fitting with various curves without an underlying
physical (e.g. Eureqa) model seems... odd. That's more voodoo
engineering/science than anything real. It doesn't surprise me that
computer scientists would propose that as an approach to data, making it
even more inappropriate.
Having well-versed engineers and physical scientists looking at curves and
striving to understand the various features with underlying well-understood
and used physical models (including abnormalities in measurements), that
seems appropriate.
The originally proposed model of long term linear drift trend plus
exponential decay of initial thermal conditions is very well understood and
accepted.
however, sometimes, looking to see what else fits might lead to insight
into what is going on "inside the box", when you don't have any information.
In general, though, I agree with you. Every year at the International
Science and Engineering Fair (and at the local and regional fairs before
it), I see people fitting a straight line to data that is fundamentally
not linear (e.g. RF signal strength vs distance, or aerodynamic drag vs
velocity, or speed of sound vs temperature)
I can sort of forgive trying to use a polynomial fit for something for
which the underlying physics says something different; especially if
there's no other choice. Square roots are a particular problem and pop
up surprisingly often: vterminal = sqrt(2*accel*distance), and are not
modeled well by a polynomial.
However, the Excel plot with the linear regression, giving coefficients
out to 5 digits and R^2 the same, is just inappropriate; particularly at
the ISEF level.
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