Chapter 9-Forecasting and Demand Planning

2. a linear regression model with more than one independent variable.
4. is a method for building a statistical model that defines a relationship between a single dependent variable and one or more independent variables, all of which are numerical.
7. consists of forecasting by expert opinion by gathering judgments and opinions of key personnel based on their experience and knowledge of the situation.
8. is a set of observations measured at successive points in time or over successive periods of time.
10. the tendency of forecasts to consistently be larger or smaller than the actual values of the time series.
13. is the underlying pattern of growth or decline in a time series.
14. are characterized by repeatable periods of ups and downs over short periods of time.
16. the length of time on which a forecast is based.
17. asking those who are close to the end consumer, such as salespeople, about the customers’ purchasing plans.
18. an average of the most recent “k” observations in a time series.
19. the process of projecting the values of one or more variables into the future.

1. is a one time variation that is explainable.
3. are regular patterns in a data series that take place over long periods of time.
5. a forecasting technique that uses a weighted average of past time-series values to forecast the value of the time series in the next period.
6. relies upon opinions and expertise of people in developing forecasts.
9. is based on the assumption that the future will be an extrapolation of the past.
11. the time-period size used in the MRP explosion process and usually are one week in length.
12. sometimes called noise) is the unexplained deviation of a time series from a predictable pattern such as a trend, seasonal, or cyclical pattern.
15. is the difference between the observed value of the time series and the forecast, or At - Ft.