Problem 4.9 (1)

xlsx

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St. John's University *

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3325

Subject

Economics

Date

Feb 20, 2024

Type

xlsx

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3

Uploaded by alifue

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LENOVO Forecasting Moving averages - 1 period moving average Num pds 3 To change the number of periods use the scrollbar, do Data Forecasts and Error Analysis Period Demand Forecast Error Absolute Squared JANUARY 1.8 FEBRUARY 1.67 1.8 -0.13 0.13 0.0169 MARCH 1.7 1.67 0.03 0.03 0.0009 APRIL 1.85 1.7 0.15 0.15 0.0225 MAY 1.9 1.85 0.05 0.05 0.0025 JUNE 1.87 1.9 -0.03 0.03 0.0009 JULY 1.8 1.87 -0.07 0.07 0.0049 AUGUST 1.83 1.8 0.03 0.03 0.0009 SEPTEMBER 1.7 1.83 -0.13 0.13 0.0169 OCTOBER 1.65 1.7 -0.05 0.05 0.0025 NOVEMBER 1.7 1.65 0.05 0.05 0.0025 DECEMBER 1.75 1.7 0.05 0.05 0.0025 Total -0.05 0.77 0.0739 Average -0.00454545 0.07 0.00671818 Bias MAD MSE SE 0.09061518 Next period 1.75 Enter the past demands in the data area Enter the past demands in the data area
o not change the cell itself Abs Pct Err a) 07.78% 01.76% 08.11% 02.63% 01.60% 03.89% 01.64% 07.65% 03.03% 02.94% 02.86% 43.90% b) 03.99% MAPE c)
Use a 2-month moving average on all the data and plot the averages and the prices. February-March: 1.67 + 1.70 / 2 = 1.685 March-April: 1.70 + 1.85 / 2 = 1.775 April-May: 1.85 + 1.9 / 2 = 1.875 May-June: 1.9 + 1.87 / 2 = 1.885 June-July: 1.87 + 1.8 / 2 = 1.835 July-August: 1.8 + 1.83 / 2 = 1.815 August-September: 1.83 + 1.7 / 2 = 1.765 September-October: 1.7 + 1.65 / 2 = 1.675 October-November: 1.65 + 1.7 / 2 = 1.675 November-December: 1.7 + 1.75 / 2 = 1.725 Use a 3-month moving average and add the 3-month plot to the graph created in part (a). March-May: (1.67+1.70+1.85)/3 = 1.74 April-June: (1.70+1.85+1.90)/3=1.82 May-July: (1.85+1.90+1.87)/3= 1.87 June-August: (1.90+1.87+1.80)/3=1.86 July-September: (1.87+1.80+1.83)=1.83 September-November: (1.83+1.70+1.65)=1.73 October-December: (1.70+1.65+1.70)=1.68 Which is better (using the mean absolute deviation): the 2-month average or the 3-month average? Since the MAD for the 3-month moving average is lower, it indicates that the 3-month moving average is better (sm
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