Review and Discussion questions
1. Examine Exhibit 9.3 and suggest which forecasting technique you might use for
(a) bathing suits. (b) demand for new house-. (e) electrical power usage. (d) new plant’
2. In terms of the errors, why would the operations manager wish to use the least method when doing simple linear regression?
3. All forecasting methods using exponential smoothing. adaptive smoothing. and exponential smoothing including trend require starting values to initialize the equations. How would you select the starting value for say Free?
4. From the choice of simple moving average. weighted moving average. exponential smoothing, and simple regression analysis. which forecasting technique would you consider the most accurate? Why?
5. What is the main disadvantage of daily forecasting using regression analysis?
6. What are the main problems with using adaptive exponential smoothing in forecasting?
7. What is the purpose of a tracking signal?
8. What are the main differences between traditional forecasting techniques and neural networks?
9. Discuss the basic differences between the mean absolute deviation (MAD) and the standard error of the estimate?
10. What implications do the existence of forecast errors have for the search for ultra sophisticated statistical forecasting models such as neural networks?