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
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