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    Regression/Correlation

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    Solution Summary

    A manufacturing plant wants to see whether or not the method in which their customer orders are taken, affect their total sales on an average day. Below shows a table of data they have recorded data from their customer service department:

    Service person

    Phone Orders Taken

    EDI (electronic data info) Orders Taken

    Total Sales
    1 54 37 $40,250
    2 40 51 $47,300
    3 52 33 $32,150
    4 39 52 $38,000
    5 30 61 $41,200
    6 39 50 $50,550
    7 53 35 $30,050
    8 52 37 $28,500
    9 54 35 $40,100
    10 42 49 $52,600
    11 52 38 $39,400
    12 40 49 $64,250
    13 35 54 $43,400
    14 53 35 $27,500
    15 52 38 $35,200
    16 38 50 $42,450
    17 41 48 $60,200
    18 52 34 $24,300
    19 43 47 $56,150
    20 46 45 $51,300

    a). Calculate (in Excel) the mean, median, and mode for the categories: Phone orders taken, EDI orders taken, and total sales.

    b.) Do you notice any interesting aspects about these calculations.

    c). Please develop two scatter plots, one to illustrate the Phone orders taken vs. total sales, and the other to illustrate EDI orders taken vs. total sales. Add a trend line, along with the regression equation and the coefficient of determination.

    d). What would you say is the outcome of the analysis? Is the total sales affected by the method in which the orders are taken? Compare the Phone and EDI orders taken. Is there similarities, differences, or both?

    e). Would you say there is a close relationship between a higher total sales and EDI orders taken? Why or why not?

    $2.19

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