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Part 2: Cameron Company is interested in establishing the relationship between utility costs and machine hours. Data...

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Accounting

Part 2: Cameron Company is interested inestablishing the relationship between utility costs and machinehours. Data has been collected and a regression analysis preparedusing Excel. The monthly data and the regression output follow:

MonthMACHINE HOURSELECTRICITY COSTS
JAN325022080
FEB377025200
MAR247016200
APR403027600
MAY494033900
JUN429026400
JUL533029700
AUG455027300
SEP260018600
OCT481031200
NOV611037200
DEC546033300



Required:
a. Using Excel, perform a regression analysis on the above data andgenerate a summary output.  

b. What is the equation for utility costs using the regressionanalysis?

c. Prepare an estimate of utility costs for a month when 3,000machine hours are worked.


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SUMMARY OUTPUT
Regression Statistics
Multiple R                                                                                    0.96538
R Square                                                                                    0.93197
Adjusted R Square                                                                                    0.92516
Standard Error                                                                             1,710.21088
Observations                                                                                        12.00
ANOVA
df SS MS F Significance F
Regression                                                                                           1.00 400,652,987.60 400,652,987.60 136.983752100    0.000000369
Residual                                                                                        10.00     29,248,212.40       2,924,821.24
Total                                                                                        11.00 429,901,200.00
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept                                                                        4,472.2547160 2,019.3896880           2.2146566           0.0511556     -27.2258867 8,971.7353190 -27.2258867 8,971.7353190
Machine Hours (x)                                                                                5.3286755           0.4552865         11.7040058           0.0000004        4.3142340         6.3431170      4.3142340         6.3431170
(b) The regression equation is y = 4472.25 + 5.3287x
(c)   When x = 3000, y = 4472.25 + 5.3287(3000) = 20458.35

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