Question 1

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 } 	ext { Year } & 	ext { Enrollments } \\hline 	ext { 5 years ago } & 15,000 \4 	ext { years ago } & 16,000 \	ext { 3 years ago } & 18,000 \2 	ext { years ago } & 20,000 \	ext { Last year } & 21,000\end{array} Year  5 years ago 4 years ago  3 years ago 2 years ago  Last year ​ Enrollments 15,00016,00018,00020,00021,000​​  What is the forecast for this year using the least squares trend line for these data?

Accepted Answer

A)   18,750
B)   19,500
C)   21,000
D)   22,650
E)   22,800 F) B) and D)
G) None of the above

Question 2

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

Accepted Answer

A) True 
 B)False

Question 3

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 } 	ext { Year } & 	ext { Attendance } \\hline 	ext { Four years ago } & 10,000 \	ext { Three years ago } & 12,000 \	ext { Two years ago } & 18,000 \	ext { Last Year } & 20,000\end{array} Year  Four years ago  Three years ago  Two years ago  Last Year ​ Attendance 10,00012,00018,00020,000​​  What is this year's forecast using the least squares trend line for these data?

Accepted Answer

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

Question 4

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

Accepted Answer

A) True 
 B)False

Question 5

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

Accepted Answer

A) True 
 B)False

Question 6

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

Accepted Answer

The answer of Data on demand over the last few...

Question 7

Which of the following helps improve supply chain forecasting performance?

Accepted Answer

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 chainF) C) and E)
G) A) and B)

Question 8

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

Accepted Answer

A)   4
B)   3
C)   2.5
D)   2
E)   1F) C) and D)
G) A) and E)

Question 9

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

Accepted Answer

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

Question 10

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 } 	ext { Year } & 	ext { Demand } \\hline 	ext { 5 years ago } & 900 \	ext { 4 years ago } & 700 \	ext { 3 years ago } & 600 \	ext { 2 years ago } & 500 \	ext { Last year } & 300\end{array} Year  5 years ago  4 years ago  3 years ago  2 years ago  Last year ​ Demand 900700600500300​​  What is the forecast for this year using the naive approach?

Accepted Answer

A)   163
B)   180
C)   300
D)   420
E)   510 F) A) and C)
G) A) and D)

Question 11

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 } 	ext { Month } & 	ext { Number of Visits } \\hline  	ext { April } & 100 \	ext { May } & 140 \	ext { June } & 110 \	ext { July } & 150 \	ext { August } & 120 \	ext { September } & 160\end{array} Month  April  May  June  July  August  September ​ Number of Visits 100140110150120160​​  What is the monthly rate of change (slope)  of the least squares trend line for these data?

Accepted Answer

A)   320
B)   102
C)   8
D)   -.4
E)   -8 F) B) and D)
G) All of the above

Question 12

Which of the following would tend to decrease forecast accuracy?

Accepted Answer

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

Question 13

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

Accepted Answer

A) True 
 B)False  True

Question 14

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

Accepted Answer

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

Question 15

Which is not a characteristic of exponential smoothing?

Accepted Answer

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 dataF) B) and E)
G) A) and B)

Question 16

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

Accepted Answer

A)   -4
B)   4
C)   5
D)   12
E)   6F) None of the above
G) B) and E)

Question 17

Which technique is used in computing seasonal relatives?

Accepted Answer

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

Question 18

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

Accepted Answer

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) D) and E)
G) A) and B)

Question 19

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:

Accepted Answer

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

Question 20

Putting forecast errors into perspective is best done using

Accepted Answer

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

Exam 3: Forecasting

Correct Answer
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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.

Correct Answer
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Correct Answer
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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.

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

Correct Answer
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Correct Answer
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Which of the following helps improve supply chain forecasting performance?

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

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

Correct Answer
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B

Correct Answer
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Correct Answer
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Which of the following would tend to decrease forecast accuracy?

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

Correct Answer
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True

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

Which is not a characteristic of exponential smoothing?

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

Correct Answer
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Which technique is used in computing seasonal relatives?

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

Correct Answer
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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:

Correct Answer
verified

Putting forecast errors into perspective is best done using

Correct Answer
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Exam 3: Forecasting

Correct AnswerverifiedShow Answer

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

Correct AnswerverifiedShow Answer

Correct AnswerverifiedShow Answer

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

Correct AnswerverifiedShow Answer

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

Correct AnswerverifiedShow Answer

Correct AnswerverifiedShow Answer

Which of the following helps improve supply chain forecasting performance?

Correct AnswerverifiedShow Answer

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

Correct AnswerverifiedShow Answer

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

Correct AnswerverifiedB

Correct AnswerverifiedShow Answer

Correct AnswerverifiedShow Answer

Which of the following would tend to decrease forecast accuracy?

Correct AnswerverifiedShow Answer

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

Correct AnswerverifiedTrue

Correct AnswerverifiedSpring = 40.93; Summer = 29.81; Fall = 51.14; Winter = 74.37

Which is not a characteristic of exponential smoothing?

Correct AnswerverifiedShow Answer

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

Correct AnswerverifiedShow Answer

Which technique is used in computing seasonal relatives?

Correct AnswerverifiedShow Answer

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

Correct AnswerverifiedShow Answer

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:

Correct AnswerverifiedShow Answer

Putting forecast errors into perspective is best done using

Correct AnswerverifiedShow Answer

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Correct Answer
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Correct Answer
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Correct Answer
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Correct Answer
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B

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True

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

Correct Answer
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Correct Answer
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Correct Answer
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Correct Answer
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Correct Answer
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Correct Answer
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