For project 2, I used the same datasets as project 1 and used StatTools to run a regression analysis for the datasets of overhead cost.
I defined all three variables which are three independent variables, weeks, labor hours, and machine hours. Running a forward regression analysis, R-square is 0.5928 or 59.28%, which is fairly significant in regard to the independent variables.
In the analysis, I used summary, ANOVA table, regression table, and step information in “forward” window.
|
Multiple |
R-Square |
Adjusted |
StErr of |
|
|
|
Summary |
R |
R-Square |
Estimate |
|
|
|
0.9476 |
0.8979 |
0.8937 |
3246.282256 |
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|
Degrees of |
Sum of |
Mean of |
F-Ratio |
p-Value |
|
|
ANOVA Table |
Freedom |
Squares |
Squares |
|
|
Explained |
2 |
4541861097 |
2270930549 |
215.4921 |
< 0.0001 |
|
|
Unexplained |
49 |
516379075.8 |
10538348.49 |
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|
Coefficient |
Standard |
t-Value |
p-Value |
Confidence Interval 95% |
|
Regression Table |
Error |
Lower |
Upper |
|
Constant |
14630.25505 |
1977.807706 |
7.3972 |
< 0.0001 |
10655.70166 |
18604.80844 |
|
LaborHrs |
28.51615589 |
1.972428771 |
14.4574 |
< 0.0001 |
24.55241187 |
32.4798999 |
|
MachineHrs |
79.10541203 |
6.53680973 |
12.1015 |
< 0.0001 |
65.96920107 |
92.24162299 |
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|
Multiple |
R-Square |
Adjusted |
StErr of |
Entry |
|
|
Step Information |
R |
R-Square |
Estimate |
Number |
|
|
LaborHrs |
0.7699 |
0.5928 |
0.5847 |
6418.238702 |
1 |
|
|
MachineHrs |
0.9476 |
0.8979 |
0.8937 |
3246.282256 |
2 |
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From the information, I can formulate the regression equation as: overhead = 28.51(labor hours) +79.105(machine hours) +14630.255
The machine hours are statically significant since its coefficient is 79.105 with t-value, and low p-value.
Furthermore, I performed another regression analysis with the labor hour only.
|
Multiple |
R-Square |
Adjusted |
StErr of |
|
|
|
Summary |
R |
R-Square |
Estimate |
|
|
|
0.7699 |
0.5928 |
0.5847 |
6418.238702 |
|
|
|
|
|
|
|
|
|
|
Degrees of |
Sum of |
Mean of |
F-Ratio |
p-Value |
|
|
ANOVA Table |
Freedom |
Squares |
Squares |
|
|
Explained |
1 |
2998550771 |
2998550771 |
72.7913 |
< 0.0001 |
|
|
Unexplained |
50 |
2059689402 |
41193788.04 |
|
|
|
|
|
|
|
|
|
|
|
Coefficient |
Standard |
t-Value |
p-Value |
Confidence Interval 95% |
|
Regression Table |
Error |
Lower |
Upper |
|
Constant |
30764.37946 |
2888.34665 |
10.6512 |
< 0.0001 |
24962.96448 |
36565.79444 |
|
LaborHrs |
32.74504467 |
3.83800688 |
8.5318 |
< 0.0001 |
25.03618098 |
40.45390836 |
|
|
|
|
|
|
|
|
Multiple |
R-Square |
Adjusted |
StErr of |
Entry |
|
|
Step Information |
R |
R-Square |
Estimate |
Number |
|
|
LaborHrs |
0.7699 |
0.5928 |
0.5847 |
6418.238702 |
1 |
|
The regression equation has changed to be: overhead = 32.74(labor hours) +30764.37 with T-value of 8.53
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