you think that seasonality may play an important role in the real demand. (1) Please calculate the seasonality indices for four seasons. (2) If next years total demand is assumed to be 5600 units, what is your estimate for the demand in next summer?

AD AF AG AH AK MAPE 1.77 4.65 3.54 3.13 3.745 3.49% 3.795 4,40% Weighted Average Method (w1-4-1, 2-4.1.13-0.3 -0.5 Time MAD for Season Forecast Forecast Period Absolute BEEF Sum of Period Each Demand Deviation Abs. Dev period Signal 4 Spring 1 1035 53.11 4755.72 5 Summer 2 2 1095 Fall 3 1196 7 Winter 4 1094 8 Spring 1 11:39 1118.80 20.20 20.20 20.20 20.20 20.20 1.00 4.04 9 Summer 6 2 1220 1126.80 93.20 113.40 93.20 113.40 56.70 2.00 8686.24 10 Fall 7 3 1194 1180,70 13.30 126.70 13.30 126.70 42.23 3.00 175.89 11 Winter 4 1167 1186.30 19.30 107.40 19.30 146.00 36,50 2.94 372.49 12 Spring 9 5 1269 1177.60 91.40 198.80 91.40 237.40 47.48 4.19 8353.96 13 Summer 10 6 1210 1226.00 -16.00 182.80 16.00 253.40 42.23 256.00 14 Fall 11 7 1318 1221.80 96 20 279.00 996.20 349.60 49.94 5.59 9254.44 15 Winter 12 8 1195 1265.60 -700 208.40 70.60 420.20 52.53 3.97 498436 16 Spring 13 9 1246 1240.80 5.20 213.60 5.20 425.40 47.27 27.04 17 Summer 14 10 1352 1234.30 117.70 331.30 117.70 543.10 54.31 6.10 13853.29 18 Fall 15 11 1377 1301.10 75.90 407.20 75.90 619.00 56.22 7.24 5760.81 19 Winter 16 12 1300 1338.20 -38 20 369.00 38.20 657.20 54.77 6.74 1459.24 20 Spring 17 13 1341 1322.90 18.10 387.10 18.10 675,30 51.95 7.45 327.61 21 Summer 18 14 1480 1333.40 146.60 533.70 146.60 821.90 58.71 9.09 21491.56 22 Fall 19 15 1384 1410.00 26.00 507.70 26.00 847.90 56.53 8.98 676.00 23 Winter 20 16 1402 1400.10 1 1.90 509.60 1.90 849.80 53.11 9.59 3.61 24 Total 849.80 75091.58 Count 16 16 26 2 Forecast Enter Real Demand-Fon (w1)(p1)+(2)(p2)+(w3(p3)+(wa)(p4) 28 MAD = Absolute vale of Error 29 MAPE = Absolute Error/Real Demart Forecast for rent period MAD - Total MAD/Count of MAD Wi ... Provided weighted averages value 31 MSE-Total MSE/Count of MSE 1.2.03..p20=Time variable 32 4.02% 4.DON 4.21% 3.87% 3.97% 4.08% 3.792 60% 16 MA Moving Average Method (nad) ( Forecast Absolute Sumo Error Deviation Ahs. Der 51.19 Real Demand Tracking Signal Season MISE MAD Period MAPE Period 4620.65 4.15% 49.80 1241.00 Spring 1 1035 Summer 2 1095 6 Fall 3 1196 7 Winter 4 1094 8 Spring 5 1 1139 Summer 6 2 1220 10 Fall 7 1194 8 4 11 Winter 1167 12 Spring 5 1269 13 Summer 10 6 1210 14 Fall 11 7 1318 15 Winter 12 8 1195 13 9 16 Spring 1246 17 Summer 14 10 1352 18 Fall 15 11 1377 19 Winter 16 12 1300 20 Spring 13 1341 21 Summer 18 14 1480 22 | 19 15 1384 23 Winter 20 16 1402 24 25 26 Forecast ErrorReal Demand - Forecast 28 MAD = Absolute wale om MAPE Absolute Error/Heal Demand MAD - Total MAD/Count of MAD 31 MSE-Total MSE/Count of MSE 32 1105.00 34.00 1131.00 89.00 1162.25 31.75 1161.75 5.25 1180.00 89.00 1212.50 -2.50 1210.00 109.00 46.00 1248.00 -2.00 1242.25 109.75 1277.75 99.25 1292.50 7.50 1318.75 22.25 1342.50 137.50 1374,50 9.50 1376.25 25.75 Total Count 34.00 123.00 154.75 160.00 249.00 246.50 354.50 308.50 306.50 416.25 515 50 523.00 54525 682.75 692.25 718.00 34.00 89.00 31.75 5.25 89.00 2.50 108.00 46.00 2.00 109.75 99.25 7.50 22.25 137.50 5450 25.75 819.00 16 34.00 3400 123.00 61.50 154.75 51.58 160.00 40.00 249.00 25150 41.92 359.50 51.36 405.50 50.69 407.50 45.28 517.25 51.73 616.50 56.05 624.00 52.00 646 25 49.71 78175 55.98 793.25 52.88 819.00 51.19 1.00 1156.00 3.0 2.00 7921.00 7.87 3.00 1008.06 2.73 4.00 27.56 0.45 5.00 7921.00 7.54% 6.25 0.215 6.90 11664.00 8.93% 6.09 2116.00 3.71% 4.00 0.16 8.05 12045.06 8.82% 9.20 9850 56 7.77 10.06 56.25 0.585 10.97 495.06 1.69 12.20 18906.25 10.24% 13.09 90.25 0.69N 14.03 663.06 1.87 66% 73930.38 16 16 Season Period Time Variable Tracking Signal MAPE 8.70N 1 2 3 4 5 6 7 1 2 3 3 4 5 5 6 7 8 9 Spring Summer Fall Winter Spring Summer Fall Winter Spring Summer Fall Winter Spring Summer Fall 9 Winter 0 Spring 1 Summer 2 Fall 3 Winter 9 10 11 12 13 14 15 16 17 18 19 20 Exponential Smoothening Method (Alpha (Y) = 0.2) Real Demand forecast Forecast forecast Absolute Sumo MAD for IM (FR RSFE Error Deviation Abs. De Each period 1035 83.77 1095 1035.00 60.00 60.00 60.00 60.00 1196 1047.00 149.00 149,00 209.00 104.50 1094 1076.80 17.20 17.20 226.20 75.40 1139 1080.24 58.76 58.76 284.96 71.24 1220 1091.99 128.01 128.01 128.01 412.97 82.59 1194 1117.59 76.41 204.41 76.41 489.37 81.56 1167 1132.87 34.13 238 54 34.13 523.50 74.79 1269 1139.70 129.30 367 84 129 30 652.80 81.60 1210 1165.56 44.44 412.28 44.44 697.24 77.47 1318 1174.45 143.55 555.83 143.55 840.79 84.08 1195 1203.16 -8.16 547.67 8.16 84.95 77.18 1246 1201.53 592.15 44.47 893.42 74.45 1352 1210.42 141.58 733.73 141.58 1035.00 79.62 1377 1238.74 138.26 871.99 138.26 1173.27 83.80 1300 1266.39 33.61 905.60 33.61 1206.88 80.46 1341 1273.11 67.89 973.49 67.89 1274.76 79.67 1480 1286.69 193.31 1166.80 193.31 1468.07 86.36 1384 132535 58.65 1225.45 58.65 1526.72 84.82 1402 1337.08 64.92 1290.36 64.92 1591.64 83.77 Total 1591.64 Count 19 10 11 12 13 14 15 16 17 18 19 9695.05 3600.00 5.48 22201.00 295.84 6.89 3452.74 6.25% 1.55 16386.05 2.51 5837.94 6.83 3.19 1164.52 6.41N 4.51 16718.51 6.439 5.32 1974.92 6.40N 6.61 20607.19 6.32 7.10 56.56 6.46 7.95 1977.88 5.98% 9.22 20044.52 5.89 10.41 19116.64 6,09% 11.26 1129.65 6.19 1222 4608.82 5.94 13:51 37368.99 5.82% 14.45 3439.65 6.13 15.40 4214.45 5.98% 184205.87 1215 19 19 Forecast ErrorReal DY(At) (1-Y) R