By "standard distribution", I think you mean "standard Normal distribution". One way to get a random sample from such a distribution is as follows: Get a random sample x_1,...x_n from a uniform distribution on the unit interval. (this is easily done using the usual random number generators you refer to.) Then for each x_i, compute z_i satisfying
x_i=(1/sqrt(2 pi))\int_{-\infty}^z_i e^{-t^2/2}dt. (I.e. x_i=F(z_i) where F is the distribution function for a N(0,1).) Then z_1,...z_n will be a random sample from a N(0,1). You have to write a bit of code to solve for z_i, of course. I've done similar things in c, but not perl so I can't display perl code to achieve this.
The previous suggestion to add the results of several uniformly distributed random numbers is interesting; one needs independence to make use of the Central Limit Theorem, so I'm not sure exactly how to set that up, but it should be possible.
The method I described first is pretty standard.
chas

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