 When you're looking at the distribution of a quantitative or continuous variable, a histogram is usually the first choice. And that's what I have right here. And in the last video, I made histograms. Here I have it for the entire variable with all three groups combined. And then down below, I have the three groups separated out. And this is a nice way to do it. However, another alternative that truthfully I prefer is to smooth out the choppiness of this a little bit with something called a density plot. And to do that, let's simply click on the existing analysis. One of the nice things about Jmovi is that when you click on an analysis, it brings up the menu that produced it. And so here we have descriptives, I've got the four quantitative or continuous variables here. I have all the statistics turned off because I didn't want a table there. And I've got histogram right down here. Now the reason histogram and density are both listed below the histograms title is because it can layer them. Now, I'm going to do that to show the relationship, but then I'm going to separate it. So I'm just going to click density right here. And this will be laid on top of the existing histograms. And so what you can see over here is our original histogram with this little blobby kind of shape over it, which is a lot like a smoothed out histogram. And you can see a similar shape on all of these. Now it doesn't follow it really exactly because it's averaging across. But you see the same general trend, strong, bimodal distributions and right here as well. Now to make it a little clearer, I'm actually going to turn off the histogram. That'll leave us with just the density plot. You can see the density plots without the histograms and the scale adjusts. And so it makes the pattern a little more pronounced. But that's our first indication that we get these blobs and you can see sort of unimodal, unimodal is really kind of triangular, but you know, kind of close to normal, strong bimodal, strong bimodal. And then we come down to this second set. And I'm going to do those as well, simply by clicking on the analysis. And this is where you have the four variables, but they're split by species. And again, all I need to do here is click density. And that'll lay the density charts on top of the existing histograms. And then I'll turn off the histograms. Again, I actually prefer to do density instead of histograms because it smooths out and makes the pattern a little easier to see. But you can see it does the same thing where it colors them, it stacks them by the three different groups. And I'm going to turn off histograms so we can see what it looks like without that. And this is where the pattern really kind of comes into focus. We have the three different groups. And you can see the mounds or the piles of the data, in ways that make it clear that the distributions are basically unimodal here, but they're in different locations, a little bit different in skewness, you come down to petal length and the differences become very clear. And I think that by using the smoothness of the density plot, it becomes a little easier to see the overall pattern and not get distracted by the jaggedness of the histograms. And so density plots are another really helpful way to look at a quantitative or continuous variable, either for all data at once or breaking it down by subgroups.