Answer Happy

URO Refer to the information below Question 10 for the context of this problem. Assume that the following data were collected. (You can also access the data in Excel here ) Remember that we are interested in explaining traffic using the other variables in the dataset (except for the Dealer number, which is just a label). Dealer Advertising ($100s) Size (Acres) Location Traffic 1 1 1.7 Rural 236 2 4 1.4 Suburban 346 3 12 1.7 Urban 352 1.8 18 Urban 454 4 5 19 2.1 Suburban 580 6 23 2.3 Urban 516 27 7 2 Rural 474 8 29 1 377 Urban 9 35 1.6 286 Rural 10 40 2.3 Suburban 592 11 47 1.8 Suburban 549 12 50 1.5 260 Rural 13 56 2.1 548 Suburban 14 59 1.7 Rural 177 15 61 1.8 Urban 535 16 69 2.2 Urban 630 17 71 1.3 Suburban 378 72 18 1.5 Urban 562 24 19 74 Urban 552 20 82 1.6 Rural 360 Use Excel to create a regression model relating customer traffic to advertising and size of the facility. (So for this question, we are ignoring the location type.) What is the estimated regression equation? Estimated traffic=38.95+0.53*Advertising ($100s +215.27"Size (Acres} Estimated traffic-0.13+1.11+218.37 10:11 ism218 37'S A

equation Estimated traffic=38.95+0.53*Advertising ($100s)+215.27'Size (Acres) Estimated traffic=0.13+1.11+218.37 Estimated traffic-0.13+1.11 Advertising ($100s)+218.37'Size (Acres) Estimated traffic-38.95+0.53+215.27 Estimated traffic-51.24+0.54 Advertising ($100s) + 171.28 Size (Acres)