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Autocorrelation means that the value expected at any point is highly correlated with its future values.

A) True
B) False

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Exponential smoothing models are not very accurate.

A) True
B) False

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A company wants to forecast demand using the simple moving average. If the company uses four prior yearly sales values , which of the following is the simple moving average forecast for year 2020?


A) 100.5
B) 140.0
C) 142.5
D) 145.5
E) 155.0

F) A) and D)
G) None of the above

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If the intercept value of a linear regression model is 40, the slope value is 40, and the value of X is 40, which of the following is the resulting forecast value using this model?


A) 120
B) 1,600
C) 1,640
D) 2,200
E) 64,000

F) A) and E)
G) A) and C)

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Trend lines are usually the last things considered when developing a forecast.

A) True
B) False

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You are hired as a consultant to advise a small firm on forecasting methodology. Based on your research, you find the company has a MAD of 3. It wants to have a 99.7 percent control limits on its forecasting system. Its most recent tracking signal value is 15. What should be your report to the company?


A) The forecasting model is operating acceptably.
B) The forecasting model is out of control and needs to be corrected.
C) The MAD value is incorrect.
D) The upper control value is less than 20.
E) The company is using an inappropriate forecasting methodology.

F) All of the above
G) C) and D)

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Which of the following forecasting methodologies is considered a time series forecasting technique?


A) Delphi method
B) Exponential averaging
C) Simple movement smoothing
D) Weighted moving average
E) Simulation

F) A) and B)
G) C) and E)

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If a firm produced a standard item with relatively stable demand, the smoothing constant alpha (reaction rate to differences) used in an exponential smoothing forecasting model would tend to be in which of the following ranges?


A) 5 to 10 percent
B) 20 to 50 percent
C) 20 to 80 percent
D) 60 to 120 percent
E) 90 to 100 percent

F) A) and D)
G) D) and E)

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A restriction in using linear regression is that it assumes that past data and future projections fall on or near a straight line.

A) True
B) False

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Which of the following forecasting methodologies is considered a qualitative forecasting technique?


A) Simple moving average
B) Market research
C) Linear regression
D) Exponential smoothing
E) Multiple regression

F) B) and D)
G) All of the above

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Random errors can be defined as those that cannot be explained by the forecast model being used.

A) True
B) False

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A company wants to forecast demand using the simple moving average. If the company uses three prior yearly sales values , which of the following is the simple moving average forecast for year 2020?


A) 100.5
B) 122.5
C) 133.3
D) 135.6
E) 139.3

F) C) and E)
G) B) and C)

Correct Answer

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Which of the following is not one of the basic types of forecasting?


A) Qualitative
B) Time series analysis
C) Causal relationships
D) Simulation
E) Force field analysis

F) C) and E)
G) A) and D)

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In the weighted moving average forecasting model, the weights must add up to one times the number of data points.

A) True
B) False

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Which of the following forecasting methods can be used for short-term forecasting?


A) Simple exponential smoothing
B) Delphi technique
C) Market research
D) Hoskins-Hamilton smoothing
E) Serial regression

F) A) and B)
G) C) and D)

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Heavy sales of umbrellas during a rainstorm is an example of which of the following?


A) A trend
B) A causal relationship
C) A statistical correlation
D) A coincidence
E) A fad

F) C) and E)
G) B) and C)

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Simple exponential smoothing lags changes in demand.

A) True
B) False

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A company has actual unit demand for three consecutive years of 124, 126, and 135. The respective forecasts for the same three years are 120, 120, and 130. Which of the following is the resulting MAD value that can be computed from these data?


A) 1
B) 3
C) 5
D) 15
E) 123

F) All of the above
G) C) and D)

Correct Answer

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MAD statistics can be used to generate tracking signals.

A) True
B) False

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Decomposition of a time series means identifying and separating the time series data into its components.

A) True
B) False

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