 You don't have to be a financial wizard to predict future costs, but you do need to know a company's cost equation. There are two primary methods used to predict costs at various levels of volume. They are the high-low method and regression analysis method. This short video will focus on the high-low method. Using the data from a scatter plot, we can easily identify the high-volume data and the low-volume data. The high-low method separates variable costs from total costs to determine fixed costs. Then we can construct the cost equation and predict costs at various levels of volume. It is not referring to a poker game. The first step is to divide the changes in cost by the changes in volume. We take the cost at the high level of volume and subtract the cost at the low level of volume. It is volume that determines high and low, not cost. This calculation will give us the variable cost per unit. So here is a sample data set. This is the same data that was shown in the scatter plot. Notice the volume and the cost for six months. The high level of volume is April at 50,000 miles. We also need the cost for this month, which is $63,000. We would use 63 as the high cost even if there was a month with a larger amount. Remember, it's volume that determines high and low. The low level of volume is January at 20,000 miles. The cost for January is $30,000. Okay, so high cost minus low cost is $33,000 and high volume minus low volume is 30,000 miles. When we divide the two, we get a variable cost per unit of $1.10 per mile driven. Using our data table and the variable cost per unit, we can figure out fixed costs. This can be done two ways and both give us the same information. We can take the cost at the high volume and subtract the high volume times the variable cost per unit to arrive at fixed costs. Or we can take the cost at low volume and subtract the low volume times the variable cost per unit to arrive at fixed costs. Here you can see that I've done it both ways. The high cost of $63,000 minus the high volume of 50,000 miles times $1.10 per mile equals $8,000 of fixed costs. You can see that we get the same number had we used the low amounts. Since we know the variable cost per unit and the fixed costs, we can write the cost equation. In this case, it's y equals $1.10x plus $8,000. With this information, we can predict costs at various levels of volume within the relevant range. Looking back at the scatter plot, I could now draw a more accurate line because I know the cost equation for this company. What would the total cost be at 45,000 miles? You can see the calculation results in a predicted cost of $57,500.