Items 1 thru 3 are based on the following information:
In preparing the annual profit plan for the coming year, Wilkens Company wants to determine the cost behavior pattern of the maintenance costs. Wilkens has decided to use linear regression by employing the equation y = a + bx for maintenance costs. The prior year’s data regarding maintenance hours and costs, and the result of the regression analysis are given below.
|
Average cost per hour |
$9.00 |
|
a |
684.65 |
|
b |
7.2884 |
|
Standard error of a |
49.515 |
|
Standard error of b |
.12126 |
|
Standard error of the estimate |
34.469 |
|
R2 |
.99724 |
|
Hours of activity |
Maintenance costs |
|
|
January |
480 |
$ 4,200 |
|
February |
320 |
3,000 |
|
March |
400 |
3,600 |
|
April |
300 |
2,820 |
|
May |
500 |
4,350 |
|
June |
310 |
2,960 |
|
July |
320 |
3,030 |
|
August |
520 |
4,470 |
|
September |
490 |
4,260 |
|
October |
470 |
4,050 |
|
November |
350 |
3,300 |
|
December |
340 |
3,160 |
|
Sum |
4,800 |
$43,200 |
|
Average |
400 |
$ 3,600 |
In the standard regression equation y = a + bx, the letter b is best described as a(n)
- Independent variable.
- Dependent variable.
- Constant coefficient.
- Variable coefficient.
The letter x in the standard regression equation is best described as a(n).
- Independent variable.
- Dependent variable.
- Constant coefficient.
- Coefficient of determination.
Based upon the data derived from the regression analysis, 420 maintenance hours in a month would mean the maintenance costs (rounded to the nearest dollar) would be budgeted at
- $3,780
- $3,600
- $3,790
- $3,746