Linear Prog COP4355_Part_31

Linear Prog COP4355_Part_31 - Chapter 11 Forecasting 128...

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128 (b) Abbreviated Regression Results: 22 X=1176 Y=1463 XY=43410 X =38024 Y =51977 ∑∑ () ( ) ( ) 2 43410 - 48 24.5 30.48 b = = 0.821 38024 - 48 24.5 a = 30.48 - 0.821 24.5 = 10.36 ˆ Y = 10.36 + 0.821X Month 0 10 20 30 40 50 60 0 1 02 03 04 05 06 0
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Solutions Manual and Workbook 129 11.23 (continued) (c) X Y ˆ Y ˆ Y-Y 1 12 11.18 0.82 2 10 12 -2 3 16 12.82 3.18 4 20 13.64 6.36 5 16 14.46 1.54 6 18 15.28 2.72 7 17 16.11 0.89 8 22 17.75 4.25 9 24 18.57 5.43 10 26 19.4 6.6 11 23 20.2 2.8 12 21 21 0 13 24 21.86 2.14 14 20 22.68 -2.68 15 26 23.5 2.5 16 21 23.5 -2.5 17 19 24.32 -5.32 18 14 25.14 -11.14 19 16 25.96 -9.96 20 21 26.78 -5.78 21 23 27.6 -4.6 22 26 28.43 -2.43 23 24 29.25 -5.25 24 22 30.07 -8.07 25 28 30.89 -2.89 26 22 31.71 -9.71 27 28 32.53 -4.53 28 32 33.35 -1.35 29 30 34.18 -4.18 30 28 34.99 -6.99 31 33 35.82 -2.82 32 39 36.64 2.36 33 42 37.46 4.54 34 46 38.28 7.72 35 45 39.11 5.89 36 44 39.93 4.07 37 48 42.4 5.6 38 44 41.57 2.43 39 48 42.4 5.6 40 52 43.21 8.79 41 46 44.03 1.97 42 44 44.85 -0.85
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130 Chapter 11 Forecasting 43 43 45.68 -2.68 44 47 46.5 0.5 45 49 47.32 1.68 46 50 48.14 1.86 47 48 48.96 -0.96 48 46 49.78 -3.78 (d) (e) January = (0.82 + 2.14 - 2.89 + 7.25)/4 = 1.83 February = (-2 – 2.68 – 9.71 + 2.43)/4 = -2.99 March = (3.18 + 2.5 – 4.53 + 5.6)/4 = 1.69 April = (6.36 – 2.5 - 1.35 + 8.79)4 = 2.83 May = (1.54 – 5.32 – 4.18 + 1.97)/4 = -1.5 June = (2.72 – 11.14 – 6.99 – 0.85)/4 = -4.07 July = (0.89 – 9.96 – 2.82 – 2.68)/4 = -3.64
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This note was uploaded on 11/13/2011 for the course COP 4355 taught by Professor Koslov during the Spring '10 term at University of Florida.

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Linear Prog COP4355_Part_31 - Chapter 11 Forecasting 128...

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