In Chapter 2 we look at using regression to estimate the fixed and variable portion of a cost. The R-square factor measures the correlation between independent and dependent variables. A high R-square factor indicates that we have found a good independent variable (machine hours, direct labor hours, number of units, etc.) to use to separate costs so that we can forecast the cost and then control it. Think of a cost that you need to forecast. Indicate two possible independent variables that you could use to forecast the cost. Which independent variable would have a higher correlation? Why? As an example, I need to estimate milk consumption for my family. Generally the cost is fixed each week. However, if my son comes to visit, milk consumption goes way up. So the correlation between my son coming over and milk costs is pretty high. Another variable regarding milk cost is Oreo cookie purchases. If we buy Oreos, everyone who is home drinks and dips and the milk consumption is on the rise. So the correlation between Oreo purchases and milk costs is fairly high as well. I would use the son visits as my independent variable. The Oreo purchase is not as good since only the people at home will drink milk. If someone is on a business trip, the Oreos and the milk would go untouched. There is a better correlation between the son visits and milk costs. For your responses, suggest another independent variable that could be used. For instance, perhaps a sale on milk is good variable if we were to stock-up when prices are low.