 Scatter plots use historical cost data to determine cost behavior. In this example, I can plot the data from the table to see the relationship between miles driven and total costs. Graphically, the cost data is plotted on the y-axis and the volume is plotted on the x-axis. Scatter plots help managers visually see how strong the relationship is between cost and volume, but it is nearly impossible to use a scatter plot to predict costs at various levels of volume. At best, a line can be added to see how linear the costs are. This line is an estimated cost equation, but again, it would be very hard to use this to predict costs. Note that where the line crosses the y-axis, meaning where the miles driven are zero, this is the amount of fixed costs. But I'm not really sure where that number is, so it's a good thing we have ways of predicting costs other than with a scatter plot. There are two primary methods used to predict costs at various levels of volume by using the data from a scatter plot. They are the high-low and regression analysis methods. The following two videos will demonstrate each.