The Cary Plant produces a part for agricultural equipment. The plant produces to demand rather than...

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The Cary Plant produces a part for agricultural equipment. The plant produces to demand rather than maintaining significant inventories, so there can be significant fluctuation in monthly output. One of the significant cost items is maintenance and repair (M&R) costs. M&R consists of both routine and unscheduled costs. The plant manager is trying to understand what effect production volume has on M&R costs and is getting conflicting information from the machine operators (who believe that higher output is related to higher M&R costs) and the financial staff (who say that their analyses do not show this). Data on monthly output (in machine hours) and monthly M&R costs for the most recent two fiscal years follow: Month October Machine-Hours 224,160 M&R Cost $ 56,570 November 236,040 59,380 December 397,500 24,210 January 310,560 34,290 February 385,080 36,400 March 558,960. 9,2001 April 273,300 36,640 May June 360,240 43,440 285,720 53,290 July 298,140 52,350 August 322,980 30,310 September 186,360 55,630 October 211,200 48,130 November 322,980 29,840 December 372,660 42,730 January 385,080 38,280 February 447,180 16,000 March 633,480 290 April 335,400 41,800 298,140 35,930 422,340 22,100 447,180 28,200 360,240 28,200 285,720 42,970 May June July August September. Required: b. Using Excel, estimate a linear regression with maintenance and repair (M&R) cost as the dependent variable and production (measured in machine hours) as the independent variable. Note: Negative amounts should be indicated by a minus sign. Round "Multiple R, R Square and Revenues to 5 decimal places, "Standard Error" to 1 decimal place, and "Intercept" to the nearest whole number. Regression Statistics July 298,140 52,350 August 322,980 30,310 September 186,360 55,630 October 211,200 48,130 November. 322,980 29,840 December 372,660 42,730 January 385,080 38,280 February 447,180 16,000 March 633,480 290 April 335,400 41,800 May 298,140 35,930 June 422,340 22,100 July August September Required: 447,180 28,200 360,240 28,200 285,720 42,970 b. Using Excel, estimate a linear regression with maintenance and repair (M&R) cost as the dependent variable and production (measured in machine hours) as the independent variable. Note: Negative amounts should be indicated by a minus sign. Round "Multiple R, R Square and Revenues to 5 decimal places, "Standard Error" to 1 decimal place, and "Intercept" to the nearest whole number. Regression Statistics Multiple R R Square Standard Error Observations Coefficients Intercept Revenues The Cary Plant produces a part for agricultural equipment. The plant produces to demand rather than maintaining significant inventories, so there can be significant fluctuation in monthly output. One of the significant cost items is maintenance and repair (M&R) costs. M&R consists of both routine and unscheduled costs. The plant manager is trying to understand what effect production volume has on M&R costs and is getting conflicting information from the machine operators (who believe that higher output is related to higher M&R costs) and the financial staff (who say that their analyses do not show this). Data on monthly output (in machine hours) and monthly M&R costs for the most recent two fiscal years follow: Month October Machine-Hours 224,160 M&R Cost $ 56,570 November 236,040 59,380 December 397,500 24,210 January 310,560 34,290 February 385,080 36,400 March 558,960. 9,2001 April 273,300 36,640 May June 360,240 43,440 285,720 53,290 July 298,140 52,350 August 322,980 30,310 September 186,360 55,630 October 211,200 48,130 November 322,980 29,840 December 372,660 42,730 January 385,080 38,280 February 447,180 16,000 March 633,480 290 April 335,400 41,800 298,140 35,930 422,340 22,100 447,180 28,200 360,240 28,200 285,720 42,970 May June July August September. Required: b. Using Excel, estimate a linear regression with maintenance and repair (M&R) cost as the dependent variable and production (measured in machine hours) as the independent variable. Note: Negative amounts should be indicated by a minus sign. Round "Multiple R, R Square and Revenues to 5 decimal places, "Standard Error" to 1 decimal place, and "Intercept" to the nearest whole number. Regression Statistics July 298,140 52,350 August 322,980 30,310 September 186,360 55,630 October 211,200 48,130 November. 322,980 29,840 December 372,660 42,730 January 385,080 38,280 February 447,180 16,000 March 633,480 290 April 335,400 41,800 May 298,140 35,930 June 422,340 22,100 July August September Required: 447,180 28,200 360,240 28,200 285,720 42,970 b. Using Excel, estimate a linear regression with maintenance and repair (M&R) cost as the dependent variable and production (measured in machine hours) as the independent variable. Note: Negative amounts should be indicated by a minus sign. Round "Multiple R, R Square and Revenues to 5 decimal places, "Standard Error" to 1 decimal place, and "Intercept" to the nearest whole number. Regression Statistics Multiple R R Square Standard Error Observations Coefficients Intercept Revenues