🚀 go-pugleaf

This is probably something that's a piece of cake for all you
stat-pros out there, but for a mere engineer the question requires
some thought and, possibly, some help.

I have experimental data, a calibration curve of sorts, for the
thermal output of a strain gauge.  I've fitted a 4th degree polynomial
to the data, by the method of least square errors, and I'm using
the polynomial to correct strain gauge readings taken at various
temperatures.  My quandary is that the polynomial does not pass
through the one point of which I'm dead certain, (20,0).  The instrument
with which the data were collected was zeroed at 20 C.  So, the
curve, ideally, should pass through (20,0).  

Two options are available to me.  First, I can simply change the
value of the constant term in my polynomial, so as to shift
the curve up or down by the required amount.  But this will give
me a new curve that DOES NOT minimize the squares of the errors.
Second, I can re-derive the equations such that the fitted curve
is CONSTRAINED to pass through (20,0).  (This would not be unlike
the application of boundary conditions by the theoretical method
in finite element problems.)  Doing so should insure that
the curve pass through (20,0), while still giving me coefficients
that minimize the square of the errors.  Now my questions:  

1) Is this legitimate, or am I just whistling Dixie?  

2) Is this a common thing to do?  If so, any references?

I thank you now, for your help later.  So does my employer, my wife, 
my children, my mortgage company, and the tax sucking municipality
that I live in.

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  * Anthony R. Rizzo       |                                              *
  * The FEA Group          | There's no shortage of engineers in the USA. *
  * AT&T Bell Laboratories |                                              *
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  * (201) 386-2565         |                                              *
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