An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the nalve approach. The linear trend equation is F-122-20t, and it was developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy if MAD and MSE are used? (Round your intermediate calculations and final answers to 2 decimal places)

Practical Management Science
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ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
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An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the
nalve approach. The linear trend equation is F-122-20t, and it was developed using data from periods 1 through 10. Based on data
for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy if MAD and MSE are used?
(Round your Intermediate calculations and final answers to 2 decimal places)
SEEEEEEEE
12
14
15
16
18
19
Units Sold
147
148
151
146
155
152
156
157
158
167
Back here for the Excel Data Fil
MAD (Naive)
MAD (Linear)
MSE (Naive)
MSE (Linear)
provides forecasts with less average amor and less average squared error
Transcribed Image Text:An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the nalve approach. The linear trend equation is F-122-20t, and it was developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy if MAD and MSE are used? (Round your Intermediate calculations and final answers to 2 decimal places) SEEEEEEEE 12 14 15 16 18 19 Units Sold 147 148 151 146 155 152 156 157 158 167 Back here for the Excel Data Fil MAD (Naive) MAD (Linear) MSE (Naive) MSE (Linear) provides forecasts with less average amor and less average squared error
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