In: Statistics and Probability
The accompany data shows the demand for one type of chip used in industrial equipment from a small manufacturer.
Month | New Chip Introduced | Demand |
1 | 0 | 3894 |
2 | 0 | 3489 |
3 | 0 | 6083 |
4 | 1 | 10645 |
5 | 0 | 7697 |
6 | 0 | 7711 |
7 | 0 | 5427 |
8 | 0 | 8734 |
9 | 1 | 13048 |
10 | 0 | 7271 |
11 | 0 | 8614 |
12 | 0 | 7164 |
13 | 0 | 7401 |
14 | 0 | 9689 |
15 | 1 | 14506 |
16 | 0 | 8509 |
17 | 0 | 12159 |
18 | 0 | 14696 |
19 | 1 | 18965 |
20 | 0 | 14214 |
21 | 0 | 14841 |
22 | 0 | 15304 |
23 | 0 | 16472 |
24 | 0 | 16974 |
a. Construct a chart of the data. What appears to happen when a new chip is introduced?
b. Develop a causal regression model to forecast demand that includes both time and the introduction of a new chip as explanatory variables.
c. What would the forecast be for the next month if a new chip is introduced? What would it be if a new chip is not introduced?