204 Regression Case
By: angelagu • Case Study • 490 Words • December 15, 2014 • 1,760 Views
204 Regression Case
204
Encino Com 2011 Case
1.
The company should use the departmental overhead rates to assign the overhead. Under plant-wide overhead rates method, in machine department the overhead cost is declining while the direct labor cost is increasing; but in assembly department, the overhead cost goes up with the increasing of the direct labor cost. It is obviously problematic.
I list the regression as follows:
Machine Hour Regression-Assembly Department
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.538998725 | |||||
R Square | 0.290519625 | |||||
Adjusted R Square | 0.219571588 | |||||
Standard Error | 343.0600974 | |||||
Observations | 12 | |||||
ANOVA | ||||||
| df | SS | MS | F | Significance F | |
Regression | 1 | 481920.612 | 481920.61 | 4.09482257 | 0.070558815 | |
Residual | 10 | 1176902.3 | 117690.23 | |||
Total | 11 | 1658822.92 |
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|
| |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 7029.421739 | 754.053925 | 9.3221738 | 3.0129E-06 | 5349.284892 | 8709.558586 |
X Variable 1 | 10.02869565 | 4.9559499 | 2.0235668 | 0.07055881 | -1.01384886 | 21.07124017 |
Direct Labor Cost Regression-Assembly Department
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.9739146 | |||||
R Square | 0.9485096 | |||||
Adjusted R Square | 0.9433606 | |||||
Standard Error | 92.419407 | |||||
Observations | 12 | |||||
ANOVA | ||||||
| df | SS | MS | F | Significance F | |
Regression | 1 | 1573409.4 | 1573409.4 | 184.21093 | 9.1047E-08 | |
Residual | 10 | 85413.468 | 8541.3468 | |||
Total | 11 | 1658822.9 |
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| |
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
Intercept | 4100.8809 | 328.30809 | 12.490953 | 2.002E-07 | 3369.36483 | 4832.3969 |
X Variable 1 | 0.2592961 | 0.0191046 | 13.572433 | 9.105E-08 | 0.21672839 | 0.3018639 |