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The president of State University wants to forecast student enrollments for this academic year based on the following historical data:  Year  Enrollments  5 years ago 15,0004 years ago 16,000 3 years ago 18,0002 years ago 20,000 Last year 21,000\begin{array} { l l } \text { Year } & \text { Enrollments } \\\hline \text { 5 years ago } & 15,000 \\4 \text { years ago } & 16,000 \\\text { 3 years ago } & 18,000 \\2 \text { years ago } & 20,000 \\\text { Last year } & 21,000\end{array} What is the forecast for this year using the least squares trend line for these data?


A) 18,750
B) 19,500
C) 21,000
D) 22,650
E) 22,800

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

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Removing the seasonal component from a data series (deseasonalizing) can be accomplished by dividing each data point by its appropriate seasonal relative.

A) True
B) False

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The owner of Darkest Tans Unlimited in a local mall is forecasting this month's (October's) demand for the one new tanning booth based on the following historical data:  Month  Number of Visits  April 100 May 140 June 110 July 150 August 120 September 160\begin{array} { l l } \text { Month } & \text { Number of Visits } \\\hline \text { April } & 100 \\\text { May } & 140 \\\text { June } & 110 \\\text { July } & 150 \\\text { August } & 120 \\\text { September } & 160\end{array} What is the monthly rate of change (slope) of the least squares trend line for these data?


A) 320
B) 102
C) 8
D) -.4
E) -8

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

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Given an actual demand of 105, a forecasted value of 97, and an alpha of .4, the simple exponential smoothing forecast for the next period would be:


A) 80.8.
B) 93.8.
C) 100.2.
D) 101.8.
E) 108.2.

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

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Which of the following is not a step in the forecasting process?


A) Determine the purpose and level of detail required.
B) Eliminate all assumptions.
C) Establish a time horizon.
D) Select a forecasting model.
E) Monitor the forecast.

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

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B

Forecasts help managers both to plan the system itself and to provide valuable information for using the system.

A) True
B) False

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True

The business analyst for Video Sales, Inc. wants to forecast this year's demand for DVD decoders based on the following historical data:  Year  Demand  5 years ago 900 4 years ago 700 3 years ago 600 2 years ago 500 Last year 300\begin{array} { l l } \text { Year } & \text { Demand } \\\hline \text { 5 years ago } & 900 \\\text { 4 years ago } & 700 \\\text { 3 years ago } & 600 \\\text { 2 years ago } & 500 \\\text { Last year } & 300\end{array} What is the forecast for this year using the naive approach?


A) 163
B) 180
C) 300
D) 420
E) 510

F) B) and D)
G) B) and E)

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A concert promoter is forecasting this year's attendance for one of his concerts based on the following historical data:  Year  Attendance  Four years ago 10,000 Three years ago 12,000 Two years ago 18,000 Last Year 20,000\begin{array} { l l } \text { Year } & \text { Attendance } \\\hline \text { Four years ago } & 10,000 \\\text { Three years ago } & 12,000 \\\text { Two years ago } & 18,000 \\\text { Last Year } & 20,000\end{array} What is this year's forecast using the least squares trend line for these data?


A) 20,000
B) 21,000
C) 22,000
D) 23,000
E) 24,000

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

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Putting forecast errors into perspective is best done using


A) exponential smoothing.
B) MAPE.
C) linear decision rules.
D) MAD.
E) hindsight.

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

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Given forecast errors of 5, 0, -4, and 3, what is the bias?


A) -4
B) 4
C) 5
D) 12
E) 6

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

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The purpose of the forecast should be established first so that the level of detail, amount of resources, and accuracy level can be understood.

A) True
B) False

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Data on demand over the last few years are available as follows:  Time Period  Demand 7 years ago 76 years ago 28 5 years ago 21 4 years ago 42 3 years ago 35 2 years ago 56 Last year 49\begin{array} { l l } \text { Time Period } & \text { Demand } \\\hline 7 \text { years ago } & 7 \\6 \text { years ago } & 28 \\\text { 5 years ago } & 21 \\\text { 4 years ago } & 42 \\\text { 3 years ago } & 35 \\\text { 2 years ago } & 56 \\\text { Last year } & 49\end{array} What would this year's forecast be if we were using the naive approach?

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Which of the following would tend to decrease forecast accuracy?


A) a reduction in demand variability
B) a shortening of the forecast time horizon
C) an attempt to forecast demand for a group of similar items rather than an individual item
D) a change in the underlying causal system

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

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Data on the last three years of demand are available as follows:  Season  Year  Spring  Summer  Fall  Winter  Three years ago 18102642 Two years ago 26183450 Last year 34264258\begin{array} { l l l l l } &&& { \text { Season } } \\\text { Year } & \text { Spring } & \text { Summer } & \text { Fall } & \text { Winter } \\\hline \text { Three years ago } & 18 & 10 & 26 & 42 \\\text { Two years ago } & 26 & 18 & 34 & 50 \\\text { Last year } & 34 & 26 & 42 & 58\end{array} What is this year's seasonally adjusted forecast for each season?

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Spring = 40.93; Summer = 29.81; Fall = 51.14; Winter = 74.37

Which technique is used in computing seasonal relatives?


A) double smoothing
B) Delphi
C) mean squared error
D) centered moving average
E) exponential smoothing

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

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Which of the following helps improve supply chain forecasting performance?


A) contracts that require supply chain members to formulate long-term forecasts
B) penalties for supply chain members that adjust forecasts
C) sharing forecasts or demand data across the supply chain
D) increasing lead times for critical supply chain members
E) increasing the number of suppliers at critical junctures in the supply chain

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

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Given forecast errors of 5, 0, -4, and 3, what is the mean absolute deviation?


A) 4
B) 3
C) 2.5
D) 2
E) 1

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

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Which of the following would be an advantage of using a sales force composite to develop a demand forecast?


A) The sales staff is least affected by changing customer needs.
B) The sales force can easily distinguish between customer desires and probable actions.
C) The sales staff is often aware of customers' future plans.
D) Salespeople are least likely to be influenced by recent events.
E) Salespeople are least likely to be biased by sales quotas.

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

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A control chart involves setting action limits for cumulative forecast error.

A) True
B) False

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Which is not a characteristic of exponential smoothing?


A) smoothes random variations in the data
B) weights each historical value equally
C) has an easily altered weighting scheme
D) has minimal data storage requirements
E) smoothes real variations in the data

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

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