 wouldn't you like to be able to predict the future or at least try to guess how things are going to happen very soon. One way to do this is with using scatter plots and associations between two quantitative or scaled variables. In this example, I'm looking at the number of sales in quarter one and the number of sales in quarter two, these are totally made up numbers. But I want to show you how to build a scatter plot and get some predictive value out of it. Now, when I take these data, and I just click on insert chart by default, it gives me the two line charts, which is definitely not what I want. I want to see how they connect one with another. So I click here on chart type. And one of the suggested charts is a scatter plot. And this lets you see the connection between sales in quarter one and sales in quarter two. So for instance, we got one quarter here that was really low in quarter one, it's about a 90 but super high in quarter two. So things went better. A lot of the others, it was just kind of uniform that quarter two seem to be pretty consistent. Now I do want to show you a couple of ways to modify these charts that might make it work better for your presentations. The first of these is that I'm going to come in and I'm going to change just for instance, the colors, I'm going to change it to red. And then I'm going to take this option right here and add a trend line. What this is a straight line that goes to the data that summarizes the relationship between the two. And because we've got this really unusual score over here that's super low on x and super high on y, we end up with a downhill pattern overall. I can make that a little thicker if I want to make it to four point. And you can change the color and the opacity. But I'm going to do one other thing here is going to say show our squared now. This is a little more than I really want to do when I'm talking about visualization because this is getting into actual data analysis. But this is a statistical measure of the strength of association between two variables that goes from zero to one and you read it like a proportion. So the fact that this one says trend line for sales and it says r squared equals zero point zero nine one, that tells you that 9% of the variance in quarter two sales can be accounted for by the variance in quarter one sales. It's a technical thing. But it lets you know there's an association there, but it's small. I'm going to do one other thing and then call it quits on this. I'm going to come back to this trend line, but I'm going to go to series because what I want to do is I want simply want to change the title for this, it gives custom label trend line for q two sales, I'm just going to remove that. So we just have the r squared there. And then that is a good final chart for looking at the association between two variables. If you're familiar with scatter plots, and if you understand how regression works, then this is the best way to look at the association between two quantitative variables, you can repeat it for lots of different possible associations to find the variables, they can give you the best predictive insight into what's happening in your organization.