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This exercise reinforces the learning from MindTap, where forecasts are developed using
different methods learned and compared. The results are compared both graphically and
numerically (forecast errors). More advanced Excel functions are used in this exercise. Total 18
points [Step 1] Using the data in the attached template, as a starting point: 1. Develop a 5 period
simple moving average and 7 period simple moving average forecast through Period 18. 2.
Develop a series of exponential forecasts through Period 18 with alpha of 0.40, 0.58, and 0.80. 3.
Develop a linear trend forecast through Period 18 and then only Priod 21. 4. Compute the MSE
for each forecast based on the last 10 forecasts and determine the best forecasting method. 5.
Also compute the MFE (Mean Forecast Error) and the MAE (Mean Absolute Error, a.k.a. Mean
Absolute Deviation, MAD) based on last 10 periods for the linear trend method. 6. Plot the
results on a common graph on the second worksheet "Chart of Forecasts".* (I

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  • 1. This exercise reinforces the learning from MindTap, where forecasts are developed using different methods learned and compared. The results are compared both graphically and numerically (forecast errors). More advanced Excel functions are used in this exercise. Total 18 points [Step 1] Using the data in the attached template, as a starting point: 1. Develop a 5 period simple moving average and 7 period simple moving average forecast through Period 18. 2. Develop a series of exponential forecasts through Period 18 with alpha of 0.40, 0.58, and 0.80. 3. Develop a linear trend forecast through Period 18 and then only Priod 21. 4. Compute the MSE for each forecast based on the last 10 forecasts and determine the best forecasting method. 5. Also compute the MFE (Mean Forecast Error) and the MAE (Mean Absolute Error, a.k.a. Mean Absolute Deviation, MAD) based on last 10 periods for the linear trend method. 6. Plot the results on a common graph on the second worksheet "Chart of Forecasts".* (I