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statistical description along with the data (Bevington, 1969). It should be men-
tioned that the merit functions are related to
2 distribution, and the corre-
sponding probability should be taken in account when assessing the reliability
of the results. For example, fi tting data without taking into account the statisti-
cal description of the performed fi t (the variance in the estimates of the fi t
parameters, the relation between the linear correlation coeffi cient, and a
goodness - of - fi t measure, 95% confi dence/prediction interval, etc.) is a common
problem in scientifi c practice. It does not allow the researcher or reader to
conclude whether the description of data throughout the used model is ade-
quate. Another common problem is the use of unweighted data, that is, to set
σ
χ
1 in merit function. In that case, data may lie perfectly on the fi t line, but
the calculated parameters might be unreliable or, at worst, completely wrong.
When reliable results have to be obtained, the propagation of the error must
be always taken into account.
=
REFERENCES
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1 ,
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