Analyzing Mixed Costs Using Scattergraph, High-Low, and Least-Squares Regression Methods
Odie Company manufactures a popular brand of cat repellant known as Cat-B-Gone, which it sells in gallon-size bottles with a spray attachment. The majority of Odie’s business comes from orders placed by homeowners who are trying to keep neighborhood cats out of their yards. Odie’s operating information for the first six months of the year follows:
Month | Number of Bottles Sold | Operating Cost |
January | 800 | $ 6,100 |
February | 1,000 | 7,500 |
March | 1,250 | 9,875 |
April | 1,950 | 14,050 |
May | 2,350 | 17,245 |
June | 2,825 | 23,150 |
Required:
1. Prepare a scattergraph of Odie’s operating cost and draw the line you believe best fits the data. Identify any potential outliers and explain your treatment of them.
2. Based on this graph, estimate Odie’s total fixed costs per month.
3. Using the high-low method, calculate Odie’s total fixed operating costs and variable operating cost per bottle.
4. Perform a least-squares regression analysis on Odie’s data.
5. Determine how well this regression analysis explains the data.
6. Using the regression output, create a linear equation (Y = A + BX) for estimating Odie’s operating costs.
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