**W**hen I saw this title on R-bloggers, I was wondering how “more perfect” a Normal sample could be when compared with the outcome of rnorm(n). Hence went checking the original blog on `bayestestR`

in search of more information. Which was stating nothing more than how to generate a sample is *perfectly* normal by using the `rnorm_perfect`

function. Still unsure of the meaning, I contacted one of the contributors who replied very quickly

…that’s actually a good question. I would say an empirical sample having characteristics as close as possible to a cannonic gaussian distribution.

`bayestestR`

and opened the `rnorm_perfect`

function. Which is simply the sequence of n-quantilesstats::qnorm(seq(1/n, 1 – 1/n, length.out = n), mean, sd)