Question 1

Perfect forecasts can be obtained only by using

Accepted Answer

A)  the right techniques 
B)  personnel with the right experience 
C)  a right blend of software and experience 
D)  carefully controlled conditions but are never obtained in the real world 
E)  lucky people and good systems 
A)  the right techniques 
B)  personnel with the right experience 
C)  a right blend of software and experience 
D)  carefully controlled conditions but are never obtained in the real world 
E)  lucky people and good systems D

Question 2

Weighted moving average method can be considered as a special case of exponential smoothing since both methods use

Accepted Answer

A)  weights for different actual values 
B)  same number of periods 
C)  decreasing weights 
D)  increasing weights 
E)  none of the above 
A)  weights for different actual values 
B)  same number of periods 
C)  decreasing weights 
D)  increasing weights 
E)  none of the above E

Question 3

Centered moving average is

Accepted Answer

A)  a technique for forecasting 
B)  a technique for finding a representative value corresponding to a period 
C)  used as a forecast, though not done often 
D)  moving average positioned at the center of the data from which it is derived 
E)  B and D 
A)  a technique for forecasting 
B)  a technique for finding a representative value corresponding to a period 
C)  used as a forecast, though not done often 
D)  moving average positioned at the center of the data from which it is derived 
E)  B and D E

Question 4

For the data $(0,100),(1,200),(2,220),(3,220),(4,266),(5,318)$, where the first number in parenthesis is period and the second number is the actual demand, the exponentially smoothed forecast for period 6 $\left(\mathrm{F}_{6}\right)$, with initial forecast $\left(\mathrm{F}_{0}\right)=100$ and $\alpha=0.7$, is equal to

Accepted Answer

A)  206 
B)  237.4 
C)  318 
D)  297.9 
E)  insufficient data 
A)  206 
B)  237.4 
C)  318 
D)  297.9 
E)  insufficient data

Question 5

An automatic traffic counter is set to collect data on the number of cars passing through an intersection between 9 a.m. and 10 a.m. on every Monday, alternate Fridays, and every third Thursday of the month. This data will

Accepted Answer

A)  be considered as a time series 
B)  be considered as an unconventional time series 
C)  not be considered as a time series because all days are not covered 
D)  not be considered as a time series because of unequal intervals 
E)  either C or D 
A)  be considered as a time series 
B)  be considered as an unconventional time series 
C)  not be considered as a time series because all days are not covered 
D)  not be considered as a time series because of unequal intervals 
E)  either C or D

Question 6

For the data $(0,1000),(1,1500),(2,2000),(3,2500),(4,3000),(5,3500)$, where the first number in parenthesis is $t$ and the second number is the actual demand, if we fit a trend line of the form $y t=a+b t$, then the trend line forecast for period 7 will be

Accepted Answer

A)  4500 
B)  4000 
C)  5500 
D)  3500 
E)  insufficient data 
A)  4500 
B)  4000 
C)  5500 
D)  3500 
E)  insufficient data

Question 7

For the data $(0,100),(1,200),(2,220),(3,220),(4,266),(5,318)$, where the first number in parenthesis is period and the second number is the actual demand, the exponentially smoothed forecast for period $6\left(\mathrm{~F}_{6}\right)$, with initial forecast $\left(\mathrm{F}_{0}\right)=100$, was found to be 312.3. The researcher forgot the a used in the calculations, but it is known that the a used is either 0.9 or 0.2 . What is your best guess for the $\alpha$ used, applying the properties of exponential smoothing?

Accepted Answer

A)  0.2 
B)  0.9 
C)  Either 0.2 or 0.9 
D)  Cannot be guessed 
E)  Only way is to calculate with both a and check 
A)  0.2 
B)  0.9 
C)  Either 0.2 or 0.9 
D)  Cannot be guessed 
E)  Only way is to calculate with both a and check

Question 8

Seasonality indices (seasonal relatives) can be calculated by

Accepted Answer

A)  volume/average 
B)  volume/centered moving average 
C)  centered moving average/volume 
D)  average/volume 
E)  none of the above 
A)  volume/average 
B)  volume/centered moving average 
C)  centered moving average/volume 
D)  average/volume 
E)  none of the above

Question 9

Demand data for number of packed food sold by Advanced Airlines on each day of the first two weeks of August 2005 is given in the table below.
   
(A) Using the centered moving average method, generate a set of centered moving averages using $\mathrm{n}$, the number of periods set to 3 .
(B) Fit a trend line for the centered moving average data, using $\mathrm{t}=1$ for 8-1-2005.
(C) Estimate seasonal index Monday.
(D) Make a seasonally adjusted trend line forecast for 8-15-2005.

Accepted Answer

(A) @#IMG-DLM& 
(B) Trend line

Question 10

For the data $(0,1000),(1,900),(2,800),(3,700),(4,600),(5,500)$, where the first number in parenthesis is $\mathrm{t}$ and the second number is the actual demand, if we fit a trend line of the form $y t=a+b t$, the value of a obtained using the appropriate formulae is

Accepted Answer

A)  0 
B)  900 
C)  1000 
D)  750 
E)  500 
A)  0 
B)  900 
C)  1000 
D)  750 
E)  500

Question 11

One period moving average for any set of data will be the same as the naïve forecast. (Choose the appropriate word to fill the blank.)

Accepted Answer

A)  sometimes 
B)  always 
C)  most of the times 
D)  never 
E)  cannot tell 
A)  sometimes 
B)  always 
C)  most of the times 
D)  never 
E)  cannot tell

Question 12

For the data $(0,1000),(1,900),(2,800),(3,700),(4,600),(5,500)$, where the first number in parenthesis is $\mathrm{t}$ and the second number is the actual demand, if we fit a trend line of the form $y t=a+b t$, the value of $\mathrm{b}$ obtained using the appropriate formulae is

Accepted Answer

A)  0 
B)  900 
C)  -100 
D)  100 
E)  750 
A)  0 
B)  900 
C)  -100 
D)  100 
E)  750

Question 13

In exponential smoothing the sum of the weights assigned to previous data

Accepted Answer

A)  tends to equal 1.0 
B)  equals 1.0 
C)  may be less than 1.0 
D)  may be greater than 1.0 
E)  none of the above 
A)  tends to equal 1.0 
B)  equals 1.0 
C)  may be less than 1.0 
D)  may be greater than 1.0 
E)  none of the above

Question 14

For the data $(0,100),(1,200),(2,220),(3,220),(4,250),(5,280)$, where the first number in parenthesis is $t$ and the second number is the actual demand, if we fit a trend line of the form $y t=a+b t$, the value of $b$

Accepted Answer

A)  must be positive 
B)  must be between 5 and 10 
C)  can be calculated using the formulae 
D)  must be negative 
E)  A and C 
A)  must be positive 
B)  must be between 5 and 10 
C)  can be calculated using the formulae 
D)  must be negative 
E)  A and C

Question 15

Good forecasts usually result by using choosing $a / n$

Accepted Answer

A)  appropriate process involving several steps 
B)  correct mathematical technique 
C)  correct qualitative method 
D)  experienced forecaster 
E)  none of the above 
A)  appropriate process involving several steps 
B)  correct mathematical technique 
C)  correct qualitative method 
D)  experienced forecaster 
E)  none of the above

Question 16

Using the trend line $y_{t}=20+6_{t}$, where $y t$ is the trend line forecast for period $t, y_{5}$ will be equal to

Accepted Answer

A)  20 
B)  26 
C)  30 
D)  50 
E)  10 
A)  20 
B)  26 
C)  30 
D)  50 
E)  10

Question 17

MAD and MSE for a given set of data will be

Accepted Answer

A)  about the same for all data since they are both positive 
B)  different since one is square of the other 
C)  different in general, though both will be positive 
D)  different in general, though both will be negative 
E)  none of the above 
A)  about the same for all data since they are both positive 
B)  different since one is square of the other 
C)  different in general, though both will be positive 
D)  different in general, though both will be negative 
E)  none of the above

Question 18

In exponential smoothing the actual weight assigned to previous data

Accepted Answer

A)  decreases with the age of data 
B)  increases with the age of data 
C)  is independent of the age of data 
D)  stays the same regardless of age 
E)  none of the above 
A)  decreases with the age of data 
B)  increases with the age of data 
C)  is independent of the age of data 
D)  stays the same regardless of age 
E)  none of the above

Question 19

Exponential smoothing can be considered as a special case of weighted moving average method since

Accepted Answer

A)  weights used in exponential smoothing decrease with age of data 
B)  weights used in exponential smoothing increase with age of data 
C)  weights used in exponential smoothing may be used as particular values in the weighted $\alpha$ moving average method 
D)  both are similar 
E)  none 
A)  weights used in exponential smoothing decrease with age of data 
B)  weights used in exponential smoothing increase with age of data 
C)  weights used in exponential smoothing may be used as particular values in the weighted $\alpha$ moving average method 
D)  both are similar 
E)  none

Question 20

Qualitative forecasts can be modified by

Accepted Answer

A)  user experience 
B)  user judgment 
C)  A and B 
D)  using quantitative methods 
E)  none of the above 
A)  user experience 
B)  user judgment 
C)  A and B 
D)  using quantitative methods 
E)  none of the above

Perfect forecasts can be obtained only by using

Weighted moving average method can be considered as a special case of exponential smoothing since both methods use

Centered moving average is

An automatic traffic counter is set to collect data on the number of cars passing through an intersection between 9 a.m. and 10 a.m. on every Monday, alternate Fridays, and every third Thursday of the month. This data will

For the data $(0,1000),(1,1500),(2,2000),(3,2500),(4,3000),(5,3500)$ , where the first number in parenthesis is $t$ and the second number is the actual demand, if we fit a trend line of the form $y t=a+b t$ , then the trend line forecast for period 7 will be

Seasonality indices (seasonal relatives) can be calculated by

For the data $(0,1000),(1,900),(2,800),(3,700),(4,600),(5,500)$ , where the first number in parenthesis is $\mathrm{t}$ and the second number is the actual demand, if we fit a trend line of the form $y t=a+b t$ , the value of a obtained using the appropriate formulae is

One period moving average for any set of data will be the same as the naïve forecast. (Choose the appropriate word to fill the blank.)

For the data $(0,1000),(1,900),(2,800),(3,700),(4,600),(5,500)$ , where the first number in parenthesis is $\mathrm{t}$ and the second number is the actual demand, if we fit a trend line of the form $y t=a+b t$ , the value of $\mathrm{b}$ obtained using the appropriate formulae is

In exponential smoothing the sum of the weights assigned to previous data

For the data $(0,100),(1,200),(2,220),(3,220),(4,250),(5,280)$ , where the first number in parenthesis is $t$ and the second number is the actual demand, if we fit a trend line of the form $y t=a+b t$ , the value of $b$

Good forecasts usually result by using choosing $a / n$

Using the trend line $y_{t}=20+6_{t}$ , where $y t$ is the trend line forecast for period $t, y_{5}$ will be equal to

MAD and MSE for a given set of data will be

In exponential smoothing the actual weight assigned to previous data

Exponential smoothing can be considered as a special case of weighted moving average method since

Qualitative forecasts can be modified by

Introduction to Management Science, Modeling, and Excel Spreadsheets

Linear Programming: Basic Concepts and Graphical Solutions

Linear Programming: Applications and Solutions

Linear Programming: Sensitivity Analysis, Duality, and Specialized Models

Transportation, Assignment, and Transshipment Problems

Integer Programming

Network Optimization Models

Nonlinear Optimization Models

Multi-Criteria Models

Decision Theory

Markov Analysis

Waiting Line Models

Simulation Cdrom Modules

Filters

Exam 2: Forecasting

Perfect forecasts can be obtained only by using

Weighted moving average method can be considered as a special case of exponential smoothing since both methods use

Centered moving average is

An automatic traffic counter is set to collect data on the number of cars passing through an intersection between 9 a.m. and 10 a.m. on every Monday, alternate Fridays, and every third Thursday of the month. This data will

Seasonality indices (seasonal relatives) can be calculated by

One period moving average for any set of data will be the same as the naïve forecast. (Choose the appropriate word to fill the blank.)

In exponential smoothing the sum of the weights assigned to previous data

Good forecasts usually result by using choosing a/na / na/n

Using the trend line yt=20+6ty_{t}=20+6_{t}yt​=20+6t​ , where yty tyt is the trend line forecast for period t,y5t, y_{5}t,y5​ will be equal to

MAD and MSE for a given set of data will be

In exponential smoothing the actual weight assigned to previous data

Exponential smoothing can be considered as a special case of weighted moving average method since

Qualitative forecasts can be modified by

Introduction to Management Science, Modeling, and Excel Spreadsheets

Linear Programming: Basic Concepts and Graphical Solutions

Linear Programming: Applications and Solutions

Linear Programming: Sensitivity Analysis, Duality, and Specialized Models

Transportation, Assignment, and Transshipment Problems

Integer Programming

Network Optimization Models

Nonlinear Optimization Models

Multi-Criteria Models

Decision Theory

Markov Analysis

Waiting Line Models

Simulation Cdrom Modules

Filters

Good forecasts usually result by using choosing $a / n$

Using the trend line $y_{t}=20+6_{t}$ , where $y t$ is the trend line forecast for period $t, y_{5}$ will be equal to