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Quiz Chapt 4 AGVM-G

# Quiz Chapt 4 AGVM-G - MGT 301 Operations Management Fall...

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MGT 301: Operations Management Name: Alban Mariau Fall 2008 8/50 84% Instructor: Kurt Haskell Quiz: Chapter 4 Due: Wed Oct 1, 11 PM 1. A naïve forecast for September sales of a product would be equal to the forecast for August. True False 2. The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product. True False 3. Forecasts of individual products tend to be more accurate than forecasts of product families. True False 4 . Most forecasting techniques assume that there is some underlying stability in the system. True False 5. A time-series model uses a series of past data points to make the forecast. True False 6. Cycles and random variations are both components of time series. True False 7. A naive forecast for September sales of a product would be equal to the sales in August. True False 8. Mean Squared Error and Coefficient of Correlation are two measures of the overall error of a forecasting model. True False 9. In trend projection, the trend component is the slope of the regression equation. True False 10. In trend projection, a negative regression slope is mathematically impossible. True False

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11. Seasonal indexes adjust raw data for patterns that repeat at regular time intervals. True False 12. If a quarterly seasonal index has been calculated at 1.55 for the October-December quarter, then raw data for that quarter must be multiplied by 1.55 so that the quarter can be fairly compared to other quarters. True False 13. Linear-regression analysis is a straight-line mathematical model to describe the functional relationships between independent and dependent variables. True False 14. The larger the standard error of the estimate, the more accurate the forecasting model. True False 15. A trend projection equation with a slope of 0.78 means that there is a 0.78 unit rise in Y for every unit of time that passes. True False 16. Demand cycles for individual products can be driven by product life cycles.
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