A full plot of C^{2} versus m
shows a minimum: C^{2}_{min}
at m = m_{min}.
In the example,
m_{min}is
the ** weighted mean** of the measurements obtained by minimizing C^{2},
i.e. determining the 'least-squares' (best fit) value.
Use the mouse (LHB) and move the purple square to find the
uncertainty in m_{min} (e
= m - m_{min}) obtained
from m when C^{2}
= C^{2}_{min }+1. It should
be close to 'Error(calc)', which is obtained from the formula: . Hit
'reset' to get a new set of values. |