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Costs    Sales     Orders

52.54    383        4,008

71.74    445        3,806

85.07    515        5,335

63.82    399        4,269

72.52    457        4,308

68.14    456        4,068

52.46    301        3,215

70.15    485        4,827

82.58    516        5,198

74.02    503        4,719

70.67    532        4,392

54.41    355        2,934

63.05    371        3,984

72.03    329        4,447

58.65    406        3,956

79.28    494        4,569

94.14    523        5,538

59.45    444        3,428

90.67    625        5,107

92.62    591        5,691

69.72    463        4,294

53.52    387        3,683

89.99    549        5,349

66.45    417        4,185

El E (7‘ U ; Documentl-"."."oi'(iFILE HOME iNSERT DESIGN PAGE LAVDUT REFERENCES MAILINGS REVIEW VIEW ACROBAT ‘ . — r""1 . . v .a Cover Page DI \ Q3) .5 I I hi a Store Efi g Hyperlink i3 ] Header Quick Parts @SIQnature Line TI: Equation $D Blank Page - _‘- IF Bookmark ] Mater 4 WordArt' 5-5 DateBtTime 9 Symbol .|_‘ Table Picturs Onlme Shaps SmartArt Chart Screenshat flMyApns Onlme Comment A Embed’.—| Page Break . Em“: - V W ' 'ICross-referen :e 3 Page Number ' gm . —_ Drop Cap I-I Dblect ' FlashPages 7 El X _ Text Symbols Flash A\ , G httpszfrwww-googlem-u P v E c i 5 VlFin rcaiculator- Google xi I 6% it? 5%} © i As the name suggests, a variance inflation factor (VIF) quantifies how much the Forthe sake ofunderstanding, let's verify the ralculation of the VIF far the we see that the predlctors Weight and A XBSA are highly correlated (r = 0.8?5). We can ‘ Multicollinearity in R | DataScienoe+nupsfldatascienceplus.comfmulticollinearity—in-rl - ”MSep 29, 2017 - Imperfect or less than perfect multicollinearity isthe more common problem and it .. .. the partial correlation coefiicients are given by the lormula. E 99 pts 15.3.1 6-T 3; Question Help {I A mail-order catalog business maintains a centralized warehouse, Management is cunently examining the factorsthat affectwarehouse distribution costs, The dataprovided indicate the warehouse distribution costs (in thousands of dollars), the sales, X1 (in thousands of dollars). and the number of orders received. X2. for each of the past 24 months Answer parts (a) and (b) belowa Click the Icon to View the data table, .1. Determine the VIF for each independent variable in the model‘ with VIF‘ and VIFZ being the VIF terX1 and X2, respectively, \riF1 : VIFZ: (Round to three decimal places as needed.)