The GP here did not claim a poisson was the same thing as a Gaussian. They also don’t look similar.
As far as I can tell you’re making the introductory student error of thinking the central limit theorem means any sufficiently large sample makes a distribution look normal.
Yes precisely. I’m also frankly shocked at the condescension. If you weren’t making that typical mistake then please explain the uses you meant. I would rarely use a box plot for a CLT distribution. Why? I would most often use it with a population sample I want to get the distribution of. Yes the mean of those would be a Gaussian under the CLT but it’s not useful useful as such.
Most natural distributions are not Gaussian upon sampling even if they’re bell shaped. They often have fatter tails, model some complex process, etc. The box plot is sometimes deceptive as is demonstrated in the original link. I don’t think that’s easy to argue against as they provide a totally reasonable and common sample distribution and show it failing to be descriptive of the most important features.
I fail to see how the CLT even remotely addresses the concerns or obviates them in any useful sense. The CLT and box plots aren’t very often applied together for these reasons.
As far as I can tell you’re making the introductory student error of thinking the central limit theorem means any sufficiently large sample makes a distribution look normal.