We study the level spacing distribution P(S) of 2D real random matrices
both symmetric as well as general, non-symmetric. In the general case we
restrict ourselves to Gaussian distributed matrix elements, but different
widths of the various matrix elements are admitted. The following results are
obtained: An explicit exact formula for P(S) is derived and its behaviour
close to S=0 is studied analytically, showing that there is linear level
repulsion, unless there are additional constraints for the probability
distribution of the matrix elements. The constraint of having only positive or
only negative but otherwise arbitrary non-diagonal elements leads to quadratic
level repulsion with logarithmic corrections. These findings detail and extend
our previous results already published in a preceding paper. For the {\em
symmetric} real 2D matrices also other, non-Gaussian statistical distributions
are considered. In this case we show for arbitrary statistical distribution of
the diagonal and non-diagonal elements that the level repulsion exponent ρ
is always ρ=1, provided the distribution function of the matrix elements
is regular at zero value. If the distribution function of the matrix elements
is a singular (but still integrable) power law near zero value of S, the
level spacing distribution P(S) is a fractional exponent pawer law at small
S. The tail of P(S) depends on further details of the matrix element
statistics. We explicitly work out four cases: the constant (box) distribution,
the Cauchy-Lorentz distribution, the exponential distribution and, as an
example for a singular distribution, the power law distribution for P(S) near
zero value times an exponential tail.Comment: 21 pages, no figures, submitted to Zeitschrift fuer Naturforschung