  A very simple Gaussian model is used to illustrate a new fitting result: a
linear growth of the resolution with the number N of detecting layers. This
rule is well beyond the well-known rule proportional to $\sqrt{N}$ for the
resolution of the usual fit. The effect is obtained with the appropriate form
of the variance for each hit (measurement). The model reconstructs straight
tracks with N parallel detecting layers, the track direction is the selected
parameter to test the resolution. The results of the Gaussian model are
compared with realistic simulations of silicon microstrip detectors. These
realistic simulations suggest an easy method to select the essential weights
for the fit: the lucky model. Preliminary results of the lucky model show an
excellent reproduction of the linear growth of the resolution, very similar to
that given by realistic simulations.
