`randn` returns draws from a standard normal distribution (i.e., a Gaussian with mean 0 and standard deviation 1); the n is for normal. It's then stretched to

`randn` returns draws from a standard normal distribution (i.e., a Gaussian with mean 0 and standard deviation 1); the n is for normal. It's then stretched to have an SD of 15 via multiplication, and shifted to have a mean of 100. This is Julia, but it's the same in Matlab and Numpy (np.random.randn); it'd be rnorm in R (which also lets you specify the mean and sd directly).