The following computer output presents the results of two simple regressions for the Brown’s Baskets overhead costs using (1) direct labor hours and (2) units of output (baskets) as the independent variables. Each regression has 24 data points, one data point per month for two years. Which activity base, units of output or labor hours, do you believe best explains variation in overhead costs?
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B |
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1 |
SUMMARY OUTPUT |
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2 |
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3 |
Regression Statistics |
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4 |
Multiple R |
0.73161563 |
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R Square |
0.53526143 |
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Adjusted R Square |
0.51413695 |
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Standard Error |
942.922704 |
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Observations |
24 |
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9 |
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ANOVA |
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11 |
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df |
SS |
MS |
F |
Significance F |
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12 |
Regression |
1 |
22528490.87 |
22528490.9 |
25.33844 |
4.85539E 05 |
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Residual |
22 |
19560270.97 |
889103.225 |
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14 |
Total |
23 |
42088761.84 |
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15 |
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16 |
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Coefficients |
Standard Error |
t Stat |
P value |
Lower 95% |
Upper 95% |
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Intercept |
4705.95547 |
826.1235525 |
5.696430583 |
9.94E 06 |
2992.678242 |
6419.23269 |
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Labor Hours |
8.08808907 |
1.606778337 |
5.033730468 |
4.86E 05 |
4.75583117 |
11.420347 |
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19 |
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Continue
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A |
B |
C |
D |
E |
F |
G |
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1 |
SUMMARY OUTPUT |
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2 |
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3 |
Regression St |
atistics |
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4 |
Multiple R |
0.881023603 |
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5 |
R Square |
0.77620259 |
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Adjusted R Square |
0.76602998 |
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Standard Error |
590.8985221 |
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8 |
Observations |
24 |
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9 |
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10 |
ANOVA |
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11 |
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df |
SS |
MS |
F |
Significance F |
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12 |
Regression |
1 |
26642104 |
26642104 |
76.30319 |
1.33090E 08 |
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13 |
Residual |
22 |
7681543.39 |
349161.063 |
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Total |
23 |
34323647.39 |
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15 |
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16 |
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Coefficients |
Standard Error |
t Stat |
P value |
Lower 95% |
Upper 95% |
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Intercept |
4338.878836 |
519.189015 |
8.357031275 |
2.84E 08 |
3262.14556 |
5415.61211 |
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Baskets |
5.293345397 |
0.60598082 |
8.735169864 |
1.33E 08 |
4.03661675 |
6.55007405 |
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19 |
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[[Discussion Questions]]