  We analyze the quality of the gaussian approximation to linear combinations
of n independent, identically-distributed random variables with finite fourth
moments. It turns out that there exist universal, simple linear combinations
that perform better than the sum of the variables. We also investigate the case
in which the random variables are independent, yet they are not necessarily
identically distributed.
