In a time-series decomposition of sales (in millions of units), the following trend has been estimated:
CMAT = 4.7 + 0.37(T)
The seasonal indices have been found to be:
|
Quarter |
Seasonal Index |
|
1 |
1.24 |
|
2 |
1.01 |
|
3 |
0.76 |
|
4 |
0.99 |
For the coming year the time index and cycle factors are:
|
Quarter |
T |
CF |
|
1 |
21 |
1.01 |
|
2 |
22 |
1.04 |
|
3 |
23 |
1.06 |
|
4 |
24 |
1.04 |
a. From this information prepare a forecast for each quarter of the coming year.
b. Actual sales for the year you forecast in part (a) were 17.2, 13.2, 10.8, and 14.2 for quarters 1, 2, 3, and 4, respectively. Use these actual sales figures along with your forecasts to calculate the root-mean-squared error for the forecast period.
