Computer information forecasting model

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klemetovich_week_8_11-16.xls
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11-16

Forecasting 3 period weighted moving average
Input Data Forecast Error Analysis
Period Actual value Weights Forecast Error Absolute error Squared error Absolute % error
Month 1 622 1
Month 2 418 2
Month 3 608 3
Month 4 752 547.000 205.000 205.000 42025.000 27.26%
Month 5 588 648.333 -60.333 60.333 3640.111 10.26%
Month 6 656 646.000 10.000 10.000 100.000 1.52%
Month 7 689 649.333 39.667 39.667 1573.444 5.76%
Month 8 675 661.167 13.833 13.833 191.361 2.05%
Month 9 706 676.500 29.500 29.500 870.250 4.18%
Month 10 725 692.833 32.167 32.167 1034.694 4.44%
Average 55.786 7062.123 7.92%
Next period 710.333 MAD MSE MAPE
Weights for the 3 previous months
Weighted average of the three previous months = [(3x16) + (2x12) + (1x10)]/6 = 13.667
MAD, MSE, and MAPE are measures of forecast error.
Enter the data in the cells shaded YELLOW.

11-16 Graph

11-16 Graph
Time
Value
3 period weighted moving average

11-16 Optimal Weights

Wallace Garden Supply
Forecasting 3 period weighted moving average
Input Data Forecast Error Analysis
Period Actual value Weights Forecast Error Absolute error Squared error Absolute % error
Month 1 10 0.2218
Month 2 12 0.5927
Month 3 16 0.1855
Month 4 13 12.298 0.702 0.702 0.492 5.40%
Month 5 17 14.556 2.444 2.444 5.971 14.37%
Month 6 19 14.407 4.593 4.593 21.093 24.17%
Month 7 15 16.484 -1.484 1.484 2.202 9.89%
Month 8 20 17.814 2.186 2.186 4.776 10.93%
Month 9 22 16.815 5.185 5.185 26.889 23.57%
Month 10 19 19.262 -0.262 0.262 0.069 1.38%
Month 11 21 21.000 0.000 0.000 0.000 0.00%
Month 12 19 20.036 -1.036 1.036 1.074 5.45%
Average 1.988 6.952 10.57%
Next period 20.185 MAD MSE MAPE
Sum of weights = 1.000
This column contains the optimal weights.
Target is to minimize MAPE
=SUM(C7:C9)
Enter the data in the cells shaded YELLOW.

Consider the data given in problem below.

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Day Sales Day Sales

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1 $622 6 $656

2 $418 7 $689

3 $608 8 $675

4 $752 9 $706

5 $588 10 $725

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A). If the store wants to use exponential smoothing to forecast the sales volume, what is the optimal value

of a that would minimize MAPE? What is the forecast for day 11 using this model?

B). If the store wants to use linear trend analysis to forecast the sales volume , what is the linear equation

that best fit’s the data? What is the forecast for day 11 using this model ?

C). Which of the methods analyzed would you use?

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