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Ch 04 HW 3 Forecasting problem Method: Linear Trend optimized with Solver - pick your own initial values for the y-axis intercept (a) and slope parameter (b) before optimizing the model The data for this problem is shown in the table below. Note: changes from the original problem data are highlighted in yellow. DO NOT USE the brute force method shown in Example 8 on pages 120- 121. DO NOT USE the linear regression function from Excels ToolPak or the LINEST Excel function. Set up a forecasting table and use Excel Solver to optimize it. Time (t) Actual A(t) 950 930 940 955 972 926 834 840 828 813 11dont have yet 2 10 What is the Forecast for Time Period 11 using this method?
Ch 04 HW 3 Forecasting problem Method: Exponential Smoothing with Trend Adjustment optimized with Solver The data for this problem is shown in the table below. Note: changes from the original problem data are highlighted in yellow. Time (t) Actual A(t) 950 930 940 955 972 926 834 840 828 813 11dont have yet 2 7 10 What is the value for MAPE using this method? Select one: a. 1.12% b. 1.23% c. 2.57% d. 1.47% e. 3.27% X 2.55%
math   Statistics-And-Probability   
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Time Actual Moving Average for nActaActual Forecast| * (t) A(t) 5 Forecast | 100 Actual 950 930 940 (950 +930 940 +955 9.4 2 196 972)/5 949.4 4 955 (930940955972 10.4 1.09% 926)/5 944.6 972 (940 +955 972 926 46.6 479% 834)/5 925.4 926 (955 972+926 834+ 20.6 2.22% 840)/5 905.4 834 972 +926 834+ 840 46 5.52% 828)/5 880 8 840 926 834+ 840 8288.2 0.98% 813)/5 848.2 828 10 813 Sum of | Actual-Forecast l * 100 / Actual = 1 + 1.09 + 4.79 + 2.22 + 5.52 + 0.98 = 15.6%MAPE = 15.6 / 6 = 2.6%

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