Sample(Generate random variables) from normal distribution

In the following previous posts, I mentioned about rejection sampling.

But I was a little confused when I learn rejection sampling.

Because we need a known distribution which we already know how to draw samples from.

Of course I know how to sample from uniform distribution. (e.g. by using /dev/random in unix).

But I don’t know others…

I started googling about how to draw samples from normal distribution.

I don’t know how credible it is, but it seems to be decent.

There are two steps when we want to draw a sample from a normal distribution whose mean is $\mu$ and variance is $\sigma^{2}$

Draw a sample $x$ from a normal distribution with mean 0 and variance 1 .
Transform the value $x$ to a sample from a normal distribution with mean $\mu$ and variance $\sigma^{2}$ by calculating $\sigma x \, + \, \mu$ .

Step 1 is not trivial. I think I will write about it next time.