Exam 16: Time-Series Forecasting
Exam 1: Defining and Collecting Data200 Questions
Exam 2: Organizing and Visualizing189 Questions
Exam 3: Numerical Descriptive Measures80 Questions
Exam 4: Basic Probability108 Questions
Exam 5: Discrete Probability Distributions81 Questions
Exam 6: Conthe Tinuonormausl Disdis Tributionstribution and Other38 Questions
Exam 7: Sampling Distributions62 Questions
Exam 8: Confidence Interval Estimation139 Questions
Exam 9: Fundamentals of Hypothesis Testing: One-Sample Tests133 Questions
Exam 10: Two-Sample Tests95 Questions
Exam 11: Analysis of Variance73 Questions
Exam 12: Chi-Square and Nonparametric100 Questions
Exam 13: Simple Linear Regression89 Questions
Exam 14: Introduction to Multiple113 Questions
Exam 15: Multiple Regression62 Questions
Exam 16: Time-Series Forecasting61 Questions
Exam 17: Business Analytics102 Questions
Exam 18: A Roadmap for Analyzing Data133 Questions
Exam 19: Statistical Applications in Quality Management86 Questions
Exam 20: Decision Making121 Questions
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SCENARIO 16-1
-Referring to Scenario 16-1, set up a scatter diagram (i.e., a time-series plot)with year on the
horizontal X-axis.

(Essay)
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The following is the list of MAD statistics for each of the models you have estimated from
Time-series data: 

(Multiple Choice)
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Which of the following terms describes the overall long-term tendency of a time series?
(Multiple Choice)
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When a time series appears to be increasing at an increasing rate, such that percentage
Difference from value to value is constant, the appropriate model to fit is the
(Multiple Choice)
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SCENARIO 16-2
-True or False: Referring to Scenario 16-2, advertising expenditures appear to be increasing
in a linear rather than curvilinear manner over time.

(True/False)
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SCENARIO 16-5
The number of passengers arriving at San Francisco on the Amtrak cross-country express on 6
successive Mondays were: 60, 72, 96, 84, 36, and 48.
-Referring to Scenario 16-5, the number of arrivals will be smoothed with a 3-term moving
average.The last smoothed value will be __________.
(Essay)
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SCENARIO 16-3
-Referring to Scenario 16-3, if a three-month moving average is used to smooth this series,
What would be the second calculated value?

(Multiple Choice)
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The effect of an unpredictable, rare event will be contained in the ___________ component.
(Multiple Choice)
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SCENARIO 16-3
-Referring to Scenario 16-3, if this series is smoothed using exponential smoothing with a
Smoothing constant of 1/3, how many values would it have?

(Multiple Choice)
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SCENARIO 16-5
The number of passengers arriving at San Francisco on the Amtrak cross-country express on 6
successive Mondays were: 60, 72, 96, 84, 36, and 48.
-Referring to Scenario 16-5, the number of arrivals will be smoothed with a 5-term moving
average.The first smoothed value will be __________.
(Essay)
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A model that can be used to make predictions about long-term future values of a time series
Is
(Multiple Choice)
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Which of the following statements about moving averages is not true?
(Multiple Choice)
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SCENARIO 16-14
-Referring to Scenario 16-14, using the regression equation, which of the following values
Is the best forecast for the number of contracts in the third quarter of 2014?

(Multiple Choice)
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SCENARIO 16-14
-Referring to Scenario 16-14, to obtain a forecast for the first quarter of 2014 using the
Model, which of the following sets of values should be used in the regression equation? 


(Multiple Choice)
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The overall upward or downward pattern of the data in an annual time series will be
Contained in the ____________ component.
(Multiple Choice)
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SCENARIO 16-3
-Referring to Scenario 16-3, suppose the last two smoothed values are 81 and 96 (Note: they
Are not).What would you forecast as the value of the time series for July?

(Multiple Choice)
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True or False: If a time series does not exhibit a long-term trend, the method of exponential
smoothing may be used to obtain short-term predictions about the future.
(True/False)
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True or False: Given a data set with 15 yearly observations, there are only seven 9-year
moving averages.
(True/False)
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