Forecast Error, Time Series Models, Tracking Signals

MGMT E 5070 DATA MINING AND FORECAST MANAGEMENT Professor Vaccaro 1st EXAMINATION , ( Forecast Error, Time Series Models, Tracking Signals ) NAME____________________ Solution True or False 1. T F According to the textbook, a short-term forecast typically covers a 1-year time horizon. 2. T F Regression is always a superior forecasting method to exponential smoothing. 3. T F The 3 categories of forecasting models are time series, quantitative, and qualitative. 4. T F Time-series models attempt to predict the future by using historical data. 5. T F A moving average forecasting method is a causal forecasting method. 6. T F An exponential forecasting method is a time-series forecasting method. 7. T F The Delphi method solicits input from customers or potential customers regarding their future purchasing plans. 8. T F The nave forecast for May, for example, is the actual value observed in April. 9. T F Mean absolute deviation ( MAD ) is simply the sum of the forecast errors. 10. T F Four components of time series are trend, moving average, exponential smoothing, and seasonality. 11. T F In a weighted moving average, the weights assigned must sum to 1 . 12. T F A scatter diagram for a time series may be plotted on a two-dimensional graph with the horizontal axis representing the variable to be forecast ( such as sales ). 13. T F An advantage of exponential smoothing over a simple moving average is that exponential smoothing requires one to retain less data. -2- 14. T F Time-series models rely on judgement in an attempt to incorporate qualitative or subjective factors into the forecasting model. 18. T F A trend-projection forecasting method is a causal forecasting method. 19. T F A scatter diagram