  Randomly distributed non-overlapping perfectly conducting spheres are
embedded in a conducting matrix with the concentration of inclusions $f$.
Jeffrey (1973) suggested an analytical formula valid up to $O(f^3)$ for
macroscopically isotropic random composites. A conditionally convergent sum
arose in the spatial averaging. In the present paper, we apply a method of
functional equations to random composites and correct Jeffrey's formula. The
main revision concerns the proper investigation of the conditionally convergent
sum and correction the $f^2$-term. A new model of symbolic computations is
developed in order to compute the effective conductivity tensor. The
corresponding algorithm is realized up to $O(f^{\frac{10}3})$. The obtained
formulae explicitly demonstrate the dependence of the effective conductivity
tensor on the deterministic and probabilistic distributions of inclusions in
the $f^2$-term, and in the $f^3$-term. This leads to the conclusion that some
previous formulae presented as universal, i.e., valid for all random
composites, may be actually applied only to dilute or to special composites
when interaction between inclusions do not matter.
