On the multidimensional central limit theorem

Two estimations in the central limit theorem for equally distributed random vectors in $R^s$ are given. The first one involves distribution functions (for $s=2$) and is an improvement of previous results stated in [1] and [2]. The second one concerns (for arbitrary $s$) “the distance” $\rho_2$ defined as
$$ \sup_A|P(A)-Q(A)| $$
where the supremum is taken over all measurable convex sets $A\in R^s$ (cf. [5]).