  The length of the asteroseismic timeseries obtained from the Kepler satellite
analysed here span 19 months. Kepler provides the longest continuous timeseries
currently available, which calls for a study of the influence of the increased
timespan on the accuracy and precision of the obtained results. We find that in
general a minimum of the order of 400 day long timeseries are necessary to
obtain reliable results for the global oscillation parameters in more than 95%
of the stars, but this does depend on <dnu>. In a statistical sense the quoted
uncertainties seem to provide a reasonable indication of the precision of the
obtained results in short (50-day) runs, they do however seem to be
overestimated for results of longer runs. Furthermore, the different
definitions of the global parameters used in the different methods have
non-negligible effects on the obtained values. Additionally, we show that there
is a correlation between nu_max and the flux variance. We conclude that longer
timeseries improve the likelihood to detect oscillations with automated codes
(from ~60% in 50 day runs to > 95% in 400 day runs with a slight method
dependence) and the precision of the obtained global oscillation parameters.
The trends suggest that the improvement will continue for even longer
timeseries than the 600 days considered here, with a reduction in the median
absolute deviation of more than a factor of 10 for an increase in timespan from
50 to 2000 days (the currently foreseen length of the mission). This work shows
that global parameters determined with high precision - thus from long datasets
- using different definitions can be used to identify the evolutionary state of
the stars. (abstract truncated)
