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                                                       505 W GRAND BLVD 206
                                                       CORONA CA 91720 2121
                                                           19 DECEMBER 1992

Dear reader:

One problem which recurs again and again in the engineering environment is
centered around the so-called least-squares curve fit.  The coefficient of
linear correlation, r, is between -1 and 1.  When r is close to +1 or -1, 
good correlation is indicated; a value of r close to 0 means little or no
correlation.  Some software outputs a more quantitative measure of goodness
of fit.  Two factors are used: (1) the number of points, N, and (2) the
value of the correlation coefficient, r.  The attached documentation and
computer programs explain this quantative measure of fit and provide work-
ing models.

The graphical output of many commercial statistical packages does not in-
clude the construction of error bars.  This shortfall is closely tied to
the problem of goodness of fit.  If the line of best fit misses a large
proportion of the error bars or if it misses one or more significantly,
then there is little or no correlation.  This is true despite a value of r
different from zero---if the number of data points, N, is small.  The doc-
ument provides a vehicle for the correct graphical display of statistical

It is hoped that the user of this document and the computer programs will 
be spared from the need to constantly "re-invent the wheel."

Harry A. Watson, Jr.
(909) 737-3958

maad – Mathematical Approximations and Documentation

A document describing the parameterisation of least-squares curve fitting, and showing how (using PiCTeX) to display error bars.

Version 1994-09-02
LicensesPublic Domain Software
MaintainerHarry A. Watson, Jr
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