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| 1 | |
Which phrase most closely describes the Delphi forecasting technique? |
| | A) | consumer survey |
| | B) | random individual opinions |
| | C) | group of expert's opinions |
| | D) | test markets |
| | E) | historic data |
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| 2 | |
Which of the following statements are true about time-series forecasting? |
| | A) | Time series analysis is based on the idea that the history of occurrences over time can be used to predict the future. |
| | B) | Time series analysis tries to understand the system underlying and surrounding the item being forecast. |
| | C) | Under time-series methods, demand is divided into the time-based components such as daily, weekly, etc. |
| | D) | Time series methods are useful for long-range forecasts when the demand pattern is erratic |
| | E) | A, B, and C |
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| 3 | |
Under exponential smoothing, if we want our forecast to be very responsive to recent demand, the value of alpha should be: |
| | A) | large |
| | B) | small |
| | C) | moderate |
| | D) | zero |
| | E) | the value of alpha doesn't matter |
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| 4 | |
Which of the following would not be classified as a time-series technique? |
| | A) | Simple moving average |
| | B) | Exponential smoothing |
| | C) | Box Jenkins technique |
| | D) | Regression model |
| | E) | Trend projections |
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| 5 | |
Given that the previous forecast of 65 turned out to be four units less than the actual demand. The next forecast is 66. What would be the value of alpha if the simple exponential smoothing forecast method is being used? |
| | A) | 0.02 |
| | B) | 0.4 |
| | C) | 0.04 |
| | D) | 0.25 |
| | E) | none of the above |
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| 6 | |
Which of the following would not be classified as a component of demand? |
| | A) | Trend |
| | B) | Seasonality |
| | C) | Cycle |
| | D) | Autocorrelation |
| | E) | Causal variation |
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| 7 | |
A _____ model is usually more accurate than a ______ model for medium-to-long-range forecasts. |
| | A) | Time-series decomposition, causal regression |
| | B) | Causal regression, time-series decomposition |
| | C) | Time-series decomposition, simple exponential smoothing |
| | D) | Simple exponential smoothing, time-series decomposition |
| | E) | Simple exponential smoothing, causal regression |
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| 8 | |
An accuracy measure that may be used to indicate any positive or negative bias in the forecast is: |
| | A) | Tracking signal |
| | B) | Mean absolute deviation |
| | C) | Mean squared error |
| | D) | Standard error |
| | E) | None of the above |
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| 9 | |
A forecasting method that uses several simple forecasting rules and computer simulation of these rules on past data is called: |
| | A) | Simulation |
| | B) | Input/output |
| | C) | Focus forecasting |
| | D) | Historical analog |
| | E) | None of the above |
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