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The forecasts are shown below with the actual values

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Unformatted text preview: oothing 6. The forecaster who uses MSD (mean squared deviations) to measure the effectiveness of forecasting methods would prefer method 1 that results in several smaller forecast errors to method 2 that results in one large forecast error equal to the sum of the absolute values of several small forecast errors given by method 1. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 6 Topic: Forecasting 7. When a forecaster uses multiplicative decomposition model or time series regression model she or he assumes that the time series components are changing over time. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 4 Topic: Multiplicative decomposition 1-1580 Chapter 01 - An Introduction to Business Statistics 8. Removing the seasonal affect by dividing the actual time series observation by the estimated seasonal factor associated with the time series observation is called deseasonalization. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 4 Topic: Depersonalization 9. When using moving averages to estimate the seasonal factors, we need to compute the centered moving average if there are odd number of seasons. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 4 Topic: Moving averages 10. When deseasonalizing a time series observation the actual time series observation is divided by its seasonal factor. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 4 Topic: Deseasonalizing 11. Dummy variables are used to model increasing seasonal variation. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 2 Topic: Time series regression 1-1581 Chapter 01 - An Introduction to Business Statistics 12. While a simple index is calculated by using the values of one time series, an aggregate index is computed based on the accumulated values of more than one time series. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 9 Topic: Index numbers 13. Paasche index more accurately provides a year-to-year comparison of the annual cost of selected products in the market-basket than Laspeyres index. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Hard Learning Objective: 9 Topic: Index numbers 14. Simple exponential forecasting method would not be used to forecast seasonal data. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 5 Topic: Exponential Smoothing 15. Holt - Winter's double exponential smoothing would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 6 Topic: Exponential Smoothing 1-1582 Chapter 01 - An Introduction to Business Statistics 16. Dummy variable regression would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 2 Topic: Time series regression 17. Time series decomposition method would not be used to forecast seasonal data. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 4 Topic: Decomposition 18. Cyclical variation exists when the magnitude of the seasonal swing does not depend on the level of a time series. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 1 Topic: Time series 19. A positive autocorrelation implies that negative error terms will be followed by negative error terms. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 2 Topic: Time series regression 1-1583 Chapter 01 - An Introduction to Business Statistics 20. Simple moving average method is primarily useful in determining the impact of trend on a time series. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Hard Learning Objective: 1 Topic: Time series analysis Multiple Choice Questions 21. Which of the following is not a component of time series? A. Trend B. Seasonal C. Cyclical D. Irregular E. Smoothing constant AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 1 Topic: Time series analysis 22. The no trend time series model is given by A. TRt = B0 + B1t B. TRt = B0 C. TRt = B0 + B1t + B2t2 D. TRt = B0 + B1ln(t) AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 1 Topic: Time series analysis 1-1584 Chapter 01 - An Introduction to Business Statistics 23. In the Durbin-Watson test, if the calculated d-statistic is greater than the upper value of the d-statistic, then A. We do not reject H0 which says the error terms are not autocorrelated B. We do reject H0 which says the error terms are not autocorrelated C. The test is inconclusive D. We do reject H0, which says the error terms are positiv...
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