  We apply several statistical estimators to high-resolution N-body simulations
of two currently viable cosmological models: a mixed dark matter model, having
$\Omega_\nu=0.2$ contributed by two massive neutrinos (C+2\nuDM), and a Cold
Dark Matter model with Cosmological Constant (\LambdaCDM) with $\Omega_0=0.3$
and h=0.7. Our aim is to compare simulated galaxy samples with the
Perseus-Pisces redshift survey (PPS). We consider the n-point correlation
functions (n=2-4), the N-count probability functions P_N, including the void
probability function P_0, and the underdensity probability function U_\epsilon
(where \epsilon fixes the underdensity threshold in percentage of the average).
We find that P_0 (for which PPS and CfA2 data agree) and P_1 distinguish
efficiently between the models, while U_\epsilon is only marginally
discriminatory. On the contrary, the reduced skewness and kurtosis are,
respectively, S_3\simeq 2.2 and S_4\simeq 6-7 in all cases, quite independent
of the scale, in agreement with hierarchical scaling predictions and estimates
based on redshift surveys. Among our results, we emphasize the remarkable
agreement between PPS data and C+2\nuDM in all the tests performed. In
contrast, the above \LambdaCDM model has serious difficulties in reproducing
observational data if galaxies and matter overdensities are related in a simple
way.
