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 11590 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 timeseries 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 11591 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 11592 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 11593 Chapter 01  An Introduction to Business Statistics 48. A sustained longterm 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 11594 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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 Winter '14
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