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3 aacsb analytic blooms application difficulty

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Unformatted text preview: nalysis 39. Suppose that the unadjusted seasonal factor for the month of April is 1.10. The sum of the 12 months' unadjusted seasonal factor values is 12.18. The normalized (adjusted) seasonal factor value for April is A. Larger than 1.1 B. Smaller than 1.1 C. Equal to 1.1 D. Cannot be determined with the information provided. AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 4 Topic: Seasonal factors 40. A major drawback of the aggregate price index is that A. It does not take into account the fact that some items in the market basket are purchased more frequently than others. B. It is difficult to compute. C. It is computed by using the values from a single time series or based on a single product. D. Percentage comparisons cannot be made to the base year. AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Easy Learning Objective: 9 Topic: Index numbers 1-1590 Chapter 01 - An Introduction to Business Statistics 41. Since the ____________ index employs the base period quantities in all succeeding periods, it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods. A. Simple B. Aggregate C. Laspeyres D. Paasche E. Quantity AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Easy Learning Objective: 9 Topic: Index numbers 42. Which of the following time series forecasting methods would not be used to forecast seasonal data? A. Dummy variable regression B. Simple exponential smoothing C. Time series decomposition D. Multiplicative Winter's method AACSB: Reflective Thinking Bloom's: Comprehension Difficulty: Medium Learning Objective: 2 Topic: Forecasting 43. Which of the following time-series forecasting methods would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns? A. Dummy variable regression B. Linear trend regression C. Holt Winter's double exponential smoothing D. Multiplicative Winter's method E. Both A and D AACSB: Reflective Thinking Bloom's: Comprehension Difficulty: Medium Learning Objective: 5 Topic: Exponential Smoothing 1-1591 Chapter 01 - An Introduction to Business Statistics 44. When the magnitude of the seasonal swing does not depend on the level of a time series, we call this _________ variation. A. Increasing seasonal B. Cyclical seasonal C. Constant seasonal D. Decreasing seasonal E. No seasonal AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 4 Topic: Seasonal variation 45. In the multiplicative decomposition method, the centered moving averages provide an estimate of: A. Trend x seasonal B. Trend x cycle C. Seasonal x cycle D. Trend x irregular E. Seasonal x irregular AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 4 Topic: Multiplicative decomposition 1-1592 Chapter 01 - An Introduction to Business Statistics 46. Assume that the current date is February 1, 2003. The linear regression model was applied to a monthly time series data based on the last 24 months' sales. (from January 2000 through December 2002). The following partial computer output summarizes the results. Determine the predicted sales for this month. A. 45.9 B. 42.7 C. 44.3 D. 109.1 E. 113.4 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 2 Topic: Time series regression 47. Assume that the current date is February 1, 2003. The linear regression model was applied to a monthly time series data based on the last 24 months' sales. (from January 2000 through December 2002). The following partial computer output summarizes the results. At a significance level of .05, what is the value of the rejection point in testing the slope for significance? A. 1.717 B. 1.96 C. 2.074 D. 1.645 E. 2.064 AACSB: Analytic Bloom's: Comprehension Difficulty: Medium Learning Objective: 2 Topic: Time series regression 1-1593 Chapter 01 - An Introduction to Business Statistics 48. A sustained long-term change in the level of the variable that is being forecasted per unit of time is: A. A trend B. A time series C. Seasonality D. A change due to business cycles AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 1 Topic: Time series analysis 49. Seasonal variations are periodic patterns in a time series that are repeated over time. For which one of the following time series variables, it is not possible to recognize seasonal variations? A. Quarters of the year B. Months of the year C. Days of the week D. Hours of the day E. Years AACSB: Reflective Thinking Bloom's: Comprehension Difficulty: Medium Learning Objective: 4 Topic: Seasonal variation 1-1594 Chapter 01 - An Introduction to Business Statistics 50. As you probably know, in a given week, the NYSE (New York Stock Exchange) is generally open from Monday through Friday. If we wanted to use multiple regression method with dummy variables to study the impact of the day of the week on stock market performance, we would n...
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This document was uploaded on 01/20/2014.

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