 scatterplot. This is a type of graph. It's a plot. It's another term. So it's a two-dimensional representation of the behaviors that you're recording. It shows the relative frequency or relative occurrence of these behaviors, whatever the case may be. Let me take a look here. The individual measures and the data set, oh yes, it's about data set depicted across the X and Y axis. So time, number of responses, level of something, so the number of whatever it is across something else. So it's a really simple graph. You don't actually connect anything, and usually your data points don't fall off your graph. They stay right on your graph, but somebody is having a little bit too much fun creating a scatterplot. Can you, ow, did you hear that thing thunk? I mean, it was almost a hollow sound there. So okay, we're gonna pause on the candy. So you can probably see this. So if we put this on a graph, like a Cartesian plane, then you would have all these data sets and you have the behavior goes this way, and the quantity or the frequency or the intensity, whatever goes up the X and the Y axis. Actually, from your perspective, it would be here like this, right? So, and then all the data is out there, you go, wow, look at that, data is all over the show. There's quite a bit of variability. Do not connect the lines. Okay, in a scatterplot, you don't connect the lines. You just see where things cluster. So this could be all, wow, everybody's the same. Wow, everybody's the same. Everybody's different, right? So you could get this weird, you know, nice line like this, which is what means predict, which is why we don't use means. Anyway, I could do a bunch of magic with the candy. I could also eat it, but that has nothing to do with a scatterplot. See you, folks.