  Current error estimates on kinematic parameters are based on the assumption
that the data points in the spectra follow a Poisson distribution. For
realistic data that have undergone several steps in a reduction process, this
is generally not the case. Neither is the noise distribution independent in
adjacent pixels. Hence, the error estimates on the derived kinematic parameters
will (in most cases) be smaller than the real errors. In this paper we propose
a method that makes a diagnosis of the characteristics of the observed noise
The method also offers the possibility to calculate more realistic error
estimates on kinematic parameters. The method was tested on spectroscopic
observations of NGC3258. In this particular case, the realistic errors are
almost a factor of 2 larger than the errors based on least squares statistics.
