Section 11 Operation Management Statistics

# Section 11 Operation Management Statistics -...

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005dc429758cb3fe02c7d62322fed461e7407a5b.xls sales data week sales 1 690 2 688 3 720 4 785 5 815 6 865 7 815 8 798 9 885 10 910 11 825 12 865 1 3 5 7 9 11 13 500 600 700 800 900 1000 week # # sales 500 600 700 800 900 1000 A B C D E F G H I J K L 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37

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005dc429758cb3fe02c7d62322fed461e7407a5b.xls sales data 1 3 5 7 9 11 13 week # A B C D E F G H I J K L 38 39 40
005dc429758cb3fe02c7d62322fed461e7407a5b.xls parameter calcs week y x^2 y^2 x*y 1 690 1 476100 690 2 688 4 473344 1376 3 720 9 518400 2160 4 785 16 616225 3140 5 815 25 664225 4075 6 865 36 748225 5190 7 815 49 664225 5705 8 798 64 636804 6384 9 885 81 783225 7965 10 910 100 828100 9100 11 825 121 680625 9075 12 865 144 748225 10380 78 9661 650 7837723 65240 SUMS 6.5 805.08 MEANS b1 = (E15 - (12*A16*B16)) / (C15 - (12*A16^2)) = 17.0874 b0 = B16 - (F19*A16) = 694.0152 Therefore, by regression, the single straight line which best models the entire demand time series is:

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## This note was uploaded on 01/26/2011 for the course OM 210 taught by Professor Singer during the Fall '08 term at George Mason.

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Section 11 Operation Management Statistics -...

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