>> In real life situations when information is gathered it's often the case that the information is in ordered pair form. For example, a year might be associated with some kind of quantity. And we'll see that many times in, in the problems that we'll encounter. Now because the information is in ordered pair form, we can think of the information in terms of the coordinates of points that can be plotted. So we can actually plot the points that information on a coordinate plane. And when those points are plotted it's called a scatter plot. It's because the points are scattered all over the coordinate plane a lot of times. Well it's often the case that the scatter plot will form a certain pattern. And let me give you, and I'm gonna give you an overview here. We're gonna examine all aspects of this, but I want to give you kind of a big picture view of where we're going with this. We have a, we have a scatter plot. We gather information. We plot the information. The information gives us a pattern on a graph. Now that pattern has a certain form that allows us to look at it and say, hum, I believe we can emulate or somehow come up with a, an equation that will model this information, this data. And that equation might be a linear equation. It might be a different kind of equation. And we'll see all kinds as we, as we progress through this course. But then what we'll do is we'll make the calculator, and the calculators is gonna do all the work here, but we'll make the calculator come up with the, the model or the line, which best fits the data that we have. And then once we have that equation, whose graph best fits the information, we can then make decisions about, or make some calculations, involving the two variables that are involved in the problem. And, and we can, we can extrapolate or, or find out information that is beyond the data, data set, or we can interpolate, or make decisions about information within the data set. And we'll see all of those kinds of situations as we go forward. But, all right, that's sort of the big picture. Now let's take things one thing at a time. Let's, let's go back to the scatter plot idea. Let's suppose that we gather ordered pair information, and that information plots like this. Now this is one kind of, of scatter plot. Now notice that the, the values tend to rise here, and they're more or less linear in nature. Well, the idea that the values are going up. That is, as X increase, Y is increasing. You see, this is called a positive correlation. And this is called a negative correlation, because as X increases the Y values are decreasing. All right? So positive and negative correlation. In some scatter plots there's no correlation at all. That is the, the dots are just all over the place, and so we would have no, no real correlation at all.