USA: +1 (725) 712-1730 
Sign in
Hello, I need help with interpreting the data from the table below. The main question is what problems do you see with the Fixed Cost and Variablr Cost data? The explanantion should be with regard to high-low and regression method. I am not sure but is it normal to have VC with negative amount? Thank you very much!
| Column | Expense | FC | VC | R-sq |
| 1 | Salaries | $106,866 | -$ 110 | 4.10% |
| 2 | Vacation | $ 1,194 | S 1.42 | 0.20% |
| 3 | Advertising and Training | $ 24,348 | -$0.02 | 0% |
| 4 | Supply/Tools/Laundry | $ 8,269 | -$22.27 | 9.30% |
| 5 | Freight | $ 430.34 | $ 0.32 | 0.20% |
| 6 | Vehicles | $ 1,809 | $ 0.18 | 0.00% |
| 7 | Demonstrators | $ 1,305.00 | -$6.76 | 3.90% |
| 8 | Floor Planning | $ 80,537 | -$399.63 | 28.30% |
| Computed Total | $224,758 | -$537 | ||
| 9 | Total | $224,758 | -$537 | 24.70% |
Expert Answer
Answer:
Since the high-low technique did not work, the regression technique would also not work well. Hence, the results for high-low and regression are consistent. The benefit of the regression technique is that it quantities the difficult level with the data. Here, one of simple regression, R-square measures tells the story. Focusing on the salaries, R-square measure tells us that only 4.1% of the total or mixed or semi-fixed cost is explained by NRVs. It means that cost equation developed from the historical data is not helpful in predicting the future costs, as 96% of the cost behavior through the use of equation remains unexplained.
