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Saved Help Save 6A Assignment The following information applies to the questions displayed below.] The Hard Rock Mining Company is developing cost formulas for management planning and decision- making purposes. The companys cost analyst has concluded that utilities cost is a mixed cost, and he is attempting to find a base that correlates with the cost. The controller has suggested that tons mined might be a good base to thinks that direct labor-hours would be a better base. The cost analyst has decided to try both bases an has assembled the following information use in developing a cost formula. The production superintendent disagrees; sh Direct Labor- Utilities Quarter Year 1: Tons Mined Hours Cost First Second Third Fourth 34,eee 6,400$ 64,000 4,40059,000 5,400 $ 74,000 7,400 $89,000 29,008 19,000 26,000 Year 2: First Second Third Fourth 32,000 39,800 44,000 42,000 13,800$132,000 12,800$135,600 11,800$ 99,000 14,800$140,000 K Prey 4 56
1b. Using the least-squares regression method, estimate the varilable utilities cost per ton mined and the total fixed utlities cost per quarter.Express these estimates in the form Yi a bX. (Round the Voriable cost per unit to 2 decimal places and Fixed Cost to the nearest whole dollar amount.) 06:18
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Answer #1

Y=13224+(2.59*tons)

I have solved using regression function in excel with 95% confidence interval selected, please find below

From From From From Other Existing Refresh Access Web Text Sources Connections All-Edit Links Sort Filter ngroup Subtotal Adv Get External Data Connections Sort & Filter Outline OK Input X Range Input X Range: Labels C2 | 13223.8582480659 Cancel Help Constant is Zerc Confidence Level: 95 1 Quarter tons minned Cost 2 year 1 first 3 second 4 third 5 fourth 6 Year 2: first 7 second 8 third 9 fourth 10 29,000 64,000 19,000 59,000 34,000 74, 26,000 89,000 32,000 132,00D 39,000 135,000 44,000 99,000 42,000 i 140,OOD Output options SESO Qutput Range: ONew Worksheet Ply: New Workbook SUMMARY OUTPUT Residuals standardized Residuals Residual Plots Line Fit Plots Regression s tatistics Multiple R R Square Adjusted R Square Standard Error Observations 0.664066895 Normal Probability Normal Probability Plots 0.347815649 26637.87856 12 15 ANOVA MS Significance F 17 18 19 Regression Residual Total 1 3358540554 3358540554 4.733161544 0.072501546 6 4257459446 709576574.3 7 7616000000 Coefficients Standard Error Lower 95% Upper 95% Lower 95.0% Upper 95.0% 13,2241 40535.96823 0.326225296 0.755332276-85g64.082呂 112411.7993-85954.0828 112411.7993 2.59 1.190241139 2.175583035 0.072501546-0.322946719 5.501883579-0.322946/19 5.501883579 21 r Stat P-value Intercept X Variable 1 24

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