Skew normal distribution

Okay kiddo, so do you remember learning about normal distribution? That's when we plot a bunch of numbers on a graph and they make a bell shape. Well, a skew normal distribution is kind of like that, but it's a little bit lopsided.

Imagine that you have a bunch of toys and you put them all in a pile. Now, most of them are the same size, so they'll be in the middle of the pile. But some of them are bigger or smaller than the rest, so they'll be towards the edges of the pile.

In a skew normal distribution, there are more numbers on one side of the graph than the other. So instead of looking like a perfect bell, it looks more like a bell that's been stretched out to one side. This happens because the data we're measuring is not completely symmetrical.

Now, why is this useful? Well, sometimes we need to analyze data that doesn't fit a normal distribution. By understanding skew normal distribution, we can better understand and analyze data that is lopsided or weighted towards one side. Pretty neat, huh?