CHAPTER 4: FORECASTING
TRUE/FALSE
1. Tupperware only uses both qualitative and quantitative forecasting techniques, culminating in a final forecast that is the consensus of all participating managers. False (Global company profile: Tupperware Corporation, moderate)
2. The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product. True (What is forecasting? moderate)
3. Sales forecasts are an input to financial planning, while demand forecasts impact human resource decisions. True (Types of forecasts, moderate)
4. Forecasts of individual products tend to be more accurate than forecasts of product families. False (Seven steps in the forecasting system, moderate)
5. Most forecasting techniques assume that there is some underlying stability in the system. True (Seven steps in the forecasting system, moderate)
6. The sales force composite forecasting method relies on salespersons’ estimates of expected sales. True (Forecasting approaches, easy)
7. A time-series model uses a series of past data points to make the forecast. True (Forecasting approaches, moderate)
8. The quarterly "make meeting" of Lexus dealers is an example of a sales force composite forecast. True (Forecasting approaches, easy)
9. Cycles and random variations are both components of time series. True (Time-series forecasting, easy)
10. A naive forecast for September sales of a product would be equal to the sales in August. True (Time-series forecasting, easy)
11. One advantage of exponential smoothing is the limited amount of record keeping involved. True (Time-series forecasting, moderate)
12. The larger the number of periods in the simple moving average forecasting method, the greater the method's responsiveness to changes in demand. False (Time-series forecasting, moderate)
13. Forecast including trend is an exponential smoothing technique that utilizes two smoothing constants: one for the average level of the forecast and one for its trend. True (Time-series forecasting, easy)
14. Mean Squared Error and Coefficient of Correlation are two measures of the overall error of a forecasting model. False (Time-series forecasting, easy)
15. In trend projection, the trend component is the slope of the regression equation. True (Time-series forecasting, easy)
16. In trend projection, a negative regression slope is mathematically impossible. False (Time-series forecasting, moderate)
17. Seasonal indexes adjust raw data for patterns that repeat at regular time intervals. True (Time-series forecasting, moderate)
18. 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. False (Time-series forecasting: Seasonal variation in data, moderate)
19. The best way to forecast a business cycle is by finding a leading variable. True (Time-series forecasting, moderate)
20. Linear-regression analysis is a straight-line mathematical model to describe the functional relationships between independent and dependent variables. True (Associative forecasting methods: Regression and correlation analysis, easy)
21. The larger the standard error of the estimate, the more accurate the forecasting model. False (Associative forecasting methods: Regression and correlation analysis, easy)
22. 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 (Time-series forecasting: Trend projections, moderate)
23. In a regression equation where Y is demand and X is advertising, a coefficient of determination (R2) of .70 means that 70% of the variance in advertising is explained by demand. False (Associative forecasting methods: Regression and correlation analysis, moderate)
24. Tracking limits should be within ± 8 MADs for low-volume stock items. True...
Topic: Forecasting, Regression analysis, Time series
Pages: 24 (5941 words)