As the accountant for Irish Linens Inc, you have been analyzing the accounts to determine what activity drives the manufacturing overhead costs. The previous accountant used direct labour hours, as she believed it was the most appropriate driver. However, the company has gone through significant automation, and you believe that machine hours may be the better driver. The following information has been gathered:

Required:
a) Develop an estimate of the cost function for manufacturing overhead using the high-low method for both (i) machine hours and (ii) direct labour hours. Note: Provide the variable cost component to four decimal places.

b) Develop an estimate of the cost function for manufacturing overhead using account analysis and direct labour hours. Note: Provide the variable cost component to four decimal places.

c) Develop an estimate of the cost function for manufacturing overhead using regression analysis. Choose the best cost driver — labour hours or machine hours — to develop the cost function and explain your choice. Note: Provide the variable cost component to four decimal places.

d) Which one of the estimates you developed — (a), (b), or (c) — is the most reliable? Present your explanations.

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Manufacturing overhead Machine hours 4,580 4,503 4,365 4,134 3,927 3,804 3,957 4,158 4,029 4,245 4,469 4,692 Month $1,067,869 1,074,792 1,068,344 1,044,164 1,022,968 1,037,620 1,042,640 1,032,056 1,051,244 1,054,024 1,063,254 1,072,484 January February March Аpril May June July August September October November December Using 20 observations including the above, you have run a regression analysis with the following Summary outputs: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Squa 0.864101825 0.746671964 0.72133916 Standard Error 8977.012134 Observations 20 ANOVA df MS F Significance F Regression 1 2,375,254,842 2,375,254,842 29.47450958 0.000289286 Residual 10 805,867,469 80,586, 747 Total 11 3,181,122,311 Upper 95% 923543.7883 Upper 95.0% 923543.7883 Coefficients Stondord Error t Stat P.volue Lower 95% Lower 95.0% 1.61144E-09 Intercept X Variable 1 833379.2593 40466.29719 20.59440367 743214.7303 743214.7303 51.72537774 9.527531144 5.429043155 0.000289286 30.49671544 72.95404005 30.49671544 72.95404005 Manufacturing overhead Machine hours 4,580 4,503 4,365 4,134 3,927 3,804 3,957 4,158 4,029 4,245 4,469 4,692 Month $1,067,869 1,074,792 1,068,344 1,044,164 1,022,968 1,037,620 1,042,640 1,032,056 1,051,244 1,054,024 1,063,254 1,072,484 January February March Аpril May June July August September October November December Using 20 observations including the above, you have run a regression analysis with the following Summary outputs: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Squa 0.864101825 0.746671964 0.72133916 Standard Error 8977.012134 Observations 20 ANOVA df MS F Significance F Regression 1 2,375,254,842 2,375,254,842 29.47450958 0.000289286 Residual 10 805,867,469 80,586, 747 Total 11 3,181,122,311 Upper 95% 923543.7883 Upper 95.0% 923543.7883 Coefficients Stondord Error t Stat P.volue Lower 95% Lower 95.0% 1.61144E-09 Intercept X Variable 1 833379.2593 40466.29719 20.59440367 743214.7303 743214.7303 51.72537774 9.527531144 5.429043155 0.000289286 30.49671544 72.95404005 30.49671544 72.95404005

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