Data obtained from experiments usually contain significant variations due to measurement errors. The purpose of curve
fitting is to find a smooth curve that on average fits the data points.
There is a distinction between interpolation (see menu under) "Interpolation Solutions", and curve
fitting. Interpolation can be regarded as a special case of curve fitting in which the function must go exactly through
the data points.
Curve fitting is applied to data that contain gaps, usually because of measurement errors and tries to find the best fit
to a set of given data. The curve does not necessarily pass through all the given data points.
As example of utilization at Keystone Mining Post we show the Straight Line Fit Method and a
Polynomial Curve Fitting Method for distinct order-polynomials.