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?