Question: Hook Company has accumulated data to use in preparing its annual profit plan for the upcoming year. The cost behavior pattern of the maintenance costs
Hook Company has accumulated data to use in preparing its annual profit plan for the upcoming year. The cost behavior pattern of the maintenance costs must be determined. Data regarding the machine hours and maintenance costs for the last year and the results of the regression analysis are as follows:
| Month | Maintenance Cost | Machine Hours |
|---|---|---|
| January | $ 5,040 | 620 |
| February | 3,600 | 420 |
| March | 4,320 | 520 |
| April | 3,380 | 390 |
| May | 5,220 | 650 |
| June | 3,550 | 400 |
| July | 3,640 | 430 |
| August | 5,360 | 680 |
| September | 5,110 | 640 |
| October | 4,860 | 610 |
| November | 3,960 | 460 |
| December | 3,790 | 440 |
| Sum | $ 51,830 | 6,260 |
| Average | $ 4,319 | 522 |
A staff assistant has run regression analyses on the data and obtained the following output using Excel:
REGRESSION ANALYSIS
Y(Dependent) Variable: Maintenance Cost
X (Independent) Variable: Maintenance Hours
| Regression Statistics | |
|---|---|
| Multiple R | 0.998210294 |
| R Square | 0.996423791 |
| Adjusted R Square | 0.99606617 |
| Standard Error | 47.0629563 |
| Observations | 12 |
| ANOVA | |||||
|---|---|---|---|---|---|
| df | SS | MS | F | Significance F | |
| Regression | 1 | 6171342.448 | 6171342 | 2786.257 | 1.44166E-13 |
| Residual | 10 | 22149.21856 | 2214.922 | ||
| Total | 11 | 6193491.667 |
| Coefficients | Standard Error | t Static | P-value | Lower 95% | Upper 95% | |
|---|---|---|---|---|---|---|
| Intercept | 783.7782188 | 68.34114772 | 11.46861 | 4.47E-07 | 631.504653 | 936.051785 |
| Hours | 6.777102456 | 0.12839066 | 52.78501 | 1.44E-13 | 6.491030239 | 7.06317467 |
PART 1: The Lower 95% and Upper 95% shown in the output suggests that:
Multiple Choice
We can be 95% confident that the precision of the regression equation will be within the ranges specified.
We can be 95% confident that the statistical reliability of the regression equation will be within the ranges specified.
We can be 95% confident that the coefficients of the dependent variable will be within the ranges specified.
We can be 95% confident that the coefficients of the independent variables will be within the ranges specified.
We can be 95% confident that the regression equation will be within the ranges specified.
PART 2: The p-value is a measure of:
Multiple Choice
The precision of the regression.
The reliability of the independent variable.
The accuracy of the regression predictions.
The linearity in the data.
None of these answers are correct.
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