Practical Management Science
Practical Management Science
6th Edition
ISBN: 9781337406659
Author: WINSTON, Wayne L.
Publisher: Cengage,
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Question
←
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table
Year
Year
Forecast (000)
1
4.00
1
5.00
2
7.00
3
5.00
3
2
4.6 5.56
Registrations (000)
a) Calculate the forecasted registrations for years 2 through 12 using exponential smoothing, with a smoothing constant (a) of 0.40 and a starting forecast of 5.00 for year 1 (round your responses to one decim
place):
5
4
4.00 9.00
4
5.34
6
9.00
10 11
9
8
7
6.00 10.00 13.00 14.00 12.00
9
8
6.89 8.14
7
6
5
7.49
6.48
4.80
10 11
10.08 11.64
12
11.79
b) Mean absolute deviation based on the forecast developed using the exponential smoothing method (with a smoothing constant (a) = 0.40 and a starting forecast of F₁ = 5.00) is
response to one decimal place).
registrations (round your
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Transcribed Image Text:← Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table Year Year Forecast (000) 1 4.00 1 5.00 2 7.00 3 5.00 3 2 4.6 5.56 Registrations (000) a) Calculate the forecasted registrations for years 2 through 12 using exponential smoothing, with a smoothing constant (a) of 0.40 and a starting forecast of 5.00 for year 1 (round your responses to one decim place): 5 4 4.00 9.00 4 5.34 6 9.00 10 11 9 8 7 6.00 10.00 13.00 14.00 12.00 9 8 6.89 8.14 7 6 5 7.49 6.48 4.80 10 11 10.08 11.64 12 11.79 b) Mean absolute deviation based on the forecast developed using the exponential smoothing method (with a smoothing constant (a) = 0.40 and a starting forecast of F₁ = 5.00) is response to one decimal place). registrations (round your
Expert Solution
Check Mark
Given:

A time series forecasting technique called exponential smoothing may be expanded to handle data with a systematic trend or seasonal component.

We know that, F(t) = F(t-1) + (Alpha * (A(t-1) - F(t-1)))

Here F(t-1) is the forecast for the previous period, and also A(t-1) is the actual demand for the previous period.

Absolute Deviation = ABS(Registrations - Exponential Forecast)

MAD = (SUM OF ABSOLUTE DEVIATIONS) / N

 

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