Interesting ways to generate a random normal deviate
I was thinking of ways to generate a random normal observation from a single random uniform(0,1) observation. I have at least 3 interesting ways in my head and 1 dull way to do this. I'll share some of the more interesting ways later. The dull way is to use Inverse Transform Sampling to directly transform the uniform into a normal.
Any other interesting ideas? They don't need to be implementable in practice necessarily and you can assume you have a truly random uniform deviate with exact precision.