So you're never going to, let's see, I mean, for example, you're never going to get a 7.5 in your sampling distribution of the sample mean for n is equal to 2, because it's impossible to get a 7, and it's impossible to get an 8. So you're never going to get 7.5 as, so maybe when you plot, when you plot it, maybe, you know, maybe it looks like this, but there'll be a gap at 7.5, because that's impossible, and, you know, maybe it looks something like that. So it still won't be a normal distribution when n is equal to 2. So there's a couple of interesting things here. So one thing, and I didn't mention this the first time, just because I really wanted to get the gut sense of what the central limit theorem is. The central limit theorem says as n approaches, really as it approaches infinity, then is when you get the real normal distribution. Normal distribution.