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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?

\$2.49