In: Accounting
George Caloz & Frères, located in Grenchen, Switzerland, makes prestige high-end custom watches in small lots. One of the company’s products, a platinum diving watch, goes through an etching process. The company has observed etching costs as follows over the last six weeks: |
Week | Units | Total Etching Cost | |||||
1 | 14 | $ | 27 | ||||
2 | 11 | $ | 20 | ||||
3 | 16 | $ | 30 | ||||
4 | 10 | $ | 20 | ||||
5 | 12 | $ | 25 | ||||
6 | 15 | $ | 28 | ||||
78 | $ | 150 | |||||
For planning purposes, management would like to know the amount
of variable etching cost |
Required: |
1. |
Prepare a scattergraph plot. (Place etching costs on the
vertical axis and units on the horizontal |
Instructions: | |
1. | On the graph below, use the point tool (Week 1) to plot units on the horizontal axis and total etching cost on the vertical axis. |
2. | Repeat the same process for the plotter tools (Week 2 to Week 6). |
3. | To enter exact coordinates, click on the point and enter the values of x and y. |
4. | To remove a point from the graph, click on the point and select delete option. |
2(a). | Using the least-squares regression method, estimate the
variable and fixed elements of etching cost. (Round your answers to 2 decimal places.) |
2(b). | Express the cost data in (2a) above in the form Y = a + bX. (Round your answers to 2 decimal places.) |
3. |
If the company processes thirteen units next week, what would be the expected total etching cost? (Round your intermediate and final answers to 2 decimal places.) |
2(a). | ||||||||
Week | Units (X) | Total Etching Cost Y) | ||||||
1 | 14 | $ 27.00 | ||||||
2 | 11 | $ 20.00 | ||||||
3 | 16 | $ 30.00 | ||||||
4 | 10 | $ 20.00 | ||||||
5 | 12 | $ 25.00 | ||||||
6 | 15 | $ 28.00 | ||||||
78 | $ 150.00 | |||||||
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.966987557 | |||||||
R Square | 0.935064935 | |||||||
Adjusted R Square | 0.918831169 | |||||||
Standard Error | 1.195228609 | |||||||
Observations | 6 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 1 | 82.2857143 | 82.2857143 | 57.6 | 0.00161674 | |||
Residual | 4 | 5.71428571 | 1.42857143 | |||||
Total | 5 | 88 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept = Fixed cost | 2.714285714 | 2.97666663 | 0.91185412 | 0.41342975 | -5.5502658 | 10.9788372 | -5.5502658 | 10.9788372 |
X Variable 1 = Units | 1.714285714 | 0.22587698 | 7.58946638 | 0.00161674 | 1.08715069 | 2.34142074 | 1.08715069 | 2.34142074 |
b) | ||||||||
Y = a + bX. | ||||||||
Y = 2.71 + 1.71 X | ||||||||
c) | ||||||||
Expected total etching cost = $2.71 + $1.71 x 13 units | $ 25.00 | |||||||
2)