On the real accuracy of approximation in the central limit theorem

We consider various approximations in the central limit theorem for distributions of sums of independent random variables. We study how many summands in the normalized sums guarantee the precision $10^{-3}$ for these approximations. It turns out that for the same distribution but different approximations this number varies from hundreds of thousands to a few tens.