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Fraser River Manufacturing has been trying to understand their costs for the current period and to help them determine the budgeted unit cost for manufacturing

Fraser River Manufacturing has been trying to understand their costs for the current period and to help them determine the budgeted unit cost for manufacturing for next year. The accountant has provided you with the following information for the past six months:

Production in

Month Cost Units

July $49,011 22,200

August 58,750 26,400

September 85,245 40,500

October 76,400 31,000

November 62,500 29,000

December 86,851 39,800

Required:

  1. Using the high-low method, determine the cost function for production cost for Fraser. [4 marks]
  2. Using regression analysis, determine the cost function for production cost for Fraser. (See Regression output below) [2 marks]
  3. If they were expecting to produce 27,500 units in January, what would the estimated cost be under each method (high/low and regression)? Which would you recommend Fraser use? Why? Are there any other considerations you would make in determining the estimated cost for January? [3 marks]ow
image text in transcribed
SUMMARY OUTPUT Regression Statistics Multiple R 0.967672 R Square 0.936389 X Variable 1 Residual Plot Adjusted F 0.920486 Standard | 4332.673 10000 Observatic 6 5000 Residuals ANOVA df SS MS F gnificance F 10,000 20,000 30,000 40,000 50,000 Regression 1 1.11E+09 1.11E+09 58.88172 0.001551 -5000 Residual 4 75088237 18772059 X Variable 1 Total 5 1.18E+09 Coefficientsandard Err, t Stat P-value Lower 95%Upper 95%ower 95.09pper 95.0% Intercept 5960.47 8504.583 0.700854 0.522021 -17652 29572.98 -17652 29572.98 X Variable 2.027497 0.264223 7.673442 0.001551 1.293897 2.761097 1.293897 2.761097 X Variable 1 Line Fit Plot RESIDUAL OUTPUT $100,000 $90,000 ObservationPredicted Y Residuals dard Residuals $80,000 50970.9 -1959.9 -0.50575 $70,000 2 59486.39 -736.39 -0.19002 $60,000 3 88074.1 -2829.1 -0.73004 > $50,000 4 68812.88 7587.124 1.957836 $40,000 5 64757.88 -2257.88 -0.58264 $30,000 Predicted Y 6 86654.85 196.1501 0.050616 $20,000 $10,000 SO 0 10,00020,00030,00040,00050,000 X Variable 1

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