Lesson 7: Measuring Forecast Error

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February 10, 2016 at 8:39 am  •  Posted in s16-busad360 by  •  3 Comments

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Wed, Feb 10

Review:

  • Time Series Forecasting

Presentation:

  • Forecast Error
    • MAD – mean absolute deviation
      • MAD = ∑|Actual – Forecast|/(Number of Forecasts)
    • MSE – mean square error
      • MSE = ∑(Actual – Forecast)^2/(Number of Forecasts)
    • MAD easier to interpret than MSE
    • Example Prob. 15.1 and 15.3 on p. 607

Activity:

Time Period Acres Harvested
1 140.0
2 141.7
3 134.6
4 131.7
5 131.9
6 134.3
7 135.2
8 131.0
  • Use the data above to complete the following
    • Create a linear trend model
    • Generate forecasts for Time Periods 9, 10 and 11 (3 separate forecasts)
    • Calculate forecast error using MAD and MSE assuming the following “actual” amounts
      • Time Period 9: 120.6
      • Time Period 10: 115.2
      • Time Period 11: 114.5

Assignment:

  • Repeat the activity above in Sheets or Excel.

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