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Table 8.4 Period Sales Forecast Error 1 245.8 250.8 -5.0 2 254.8 250.3 4.5 3 247

ID: 3074726 • Letter: T

Question

Table 8.4

Period

Sales

Forecast

Error   

   1   

   245.8

250.8  

   -5.0   

   2   

   254.8

250.3  

    4.5   

   3   

   247.4

250.8  

   -3.4   

   4   

   247.0

250.5  

   -3.5   

   5   

   250.4

250.1  

     .3   

   6   

    ?   

250.1  

          

Using the data in Table 8.4, what is the MAD through period 3?

a) 12.9

b) -3.90

c) 4.30

d) none of the above

Using the data in Table 8.4, what is the MAD for the forecast model?

a) -7.10

b) 3.34

d) 16.7

e) none of the above

In measuring forecasting accuracy, when the absolute error is measured as a percentage of demand, it is called

a) alpha

b) E-bar

c) MAPD

d) MAD

Table 8.5

Period

Sales

Forecast

Error   

   1   

   250.1

255.1  

-5.0

   2   

   268.1

254.6  

13.5

   3   

   254.9

256.0  

-1.1

   4   

   261.3

255.9  

   5.4

   5   

   245.3

256.3  

-11.0

   6   

    ?   

255.3  

Using the data in Table 8.5, what is the MAPD?

a) .14%

b) 2.81%

c) 13.5%

d) none of the above

Using the data in Table 8.5, what is the cumulative error?

a) 1.80

b) 34.50

c) 6.90

d) none of the above

Using the data in Table 8.5, what is the most recent tracking signal value?

a) .25

b) 1.84

c) 7.21

d) none of the above

The ideal value of MAPD is

a) 0%

b) 100

c) 1.00

d) 100%

In measuring forecasting accuracy, when the forecast errors are simply added up, it is called

a) E

b) E-bar

c) MAPD

d) MAD

If the cumulative error for a forecasting model is large and negative, then

a) the forecasts have all been too low

b) the model is forecasting too low

c) the forecasts have all been too high

d) the model has been forecasting too high

Table 8.7

Month    

Demand

January  

80

February

113

March    

70

April    

91

May      

105

Using the data in Table 8.7,

a) Compute an exponentially smoothed forecast with alpha = .20 through May.

b) Compute the forecast for the next month (June).

Table 8.8

Month    

Demand

January  

    60   

February

    68   

March    

    70   

April    

    75   

May      

    80   

Using the data in Table 8.8,

a) Compute an adjusted exponentially smoothed forecast with alpha

   = .20 and beta = .30, through May.

b) Compute the forecast for the next month (June).

Period

Sales

Forecast

Error   

   1   

   245.8

250.8  

   -5.0   

   2   

   254.8

250.3  

    4.5   

   3   

   247.4

250.8  

   -3.4   

   4   

   247.0

250.5  

   -3.5   

   5   

   250.4

250.1  

     .3   

   6   

    ?   

250.1  

          

Explanation / Answer

1.)

For period 3,

Error = -3.4

So, MAD = |Error| = 3,4

So correct option is d) None of the above

2.)

MAD for forecast model,

MAD = ( 5 + 4.5 + 3.4 + 3.5 + 0.3) / 5 = 16.7 / 5 = 3.34

So, option b is correct one

3.)

When accuracy is measured as percentage of demand it is called Mean absolute Percentage (MAPD)

So, option c is correct

4.)

Forecast error in percent is:

This is for 5 observations

Now MAPD = mean of above obervations = 2.80%( approximately) which is equal to 2.81%

So option b is correct

5.) Cumulative Error = Sum of all Error values as it is = 1.80

So, option a is correct

7) Ideal value for any error is 0

So, for MAPD ideal value is 0%

Option a is correct

1.999 5.03 0.431 2.06 4.48