Data collected on the yearly registrations for a Six Sigma seminar at the Quality College Year 1 4.00 Year Forecast (000) 2 3 7.00 5.00 1 2 5.00 4.6 4 5 4.00 9.00 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 dece place) 3 4 5.56 5.34 6 9.00 5 4.80 11 9 8 10 7 6.00 10.00 13.00 14.00 12.00 7 8 6 6.48 7.49 6.89 9 8.14 11 10 12 10.08 11.64 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 F, = 5.00) is response to one decimal place). registrations (round your
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College Year 1 4.00 Year Forecast (000) 2 3 7.00 5.00 1 2 5.00 4.6 4 5 4.00 9.00 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 dece place) 3 4 5.56 5.34 6 9.00 5 4.80 11 9 8 10 7 6.00 10.00 13.00 14.00 12.00 7 8 6 6.48 7.49 6.89 9 8.14 11 10 12 10.08 11.64 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 F, = 5.00) is response to one decimal place). registrations (round your
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...
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Expert Solution
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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