A statistical program is recommended. A sales manager collected the following data on x = years of experience and y - annual sales ($1,000s). The estimated regression equation for the Salesperson Years of Experience Annual Sales ($1,000s) 1 80 2 3 97 3 4 97 4 4 102 5 103 6 8 111 7 10 119 8 10 128 9 11 117 10 13 136 (a) Compute the residuals. Years of Experience Annual Sales ($1,000) Residuals 1 80 3 97 4 97 102 6 103 B 111 10 119 10 128 11 117 13 136 Consult 16 12 13 1 + . Real . . . - -5 - 12 -10 14 2 5 . 1 116 2 . 19 13 14 10 12 Experience . 30 13 10 af Expo Years Years of per Yes ) De mesto u them the recipe The plot gestalten in the medicating that the outer The usual patterns the dog that the termine de The protests a generally and of respect that the room The losest generally and allocating that the enero The posts on the more 1) Com the resour Years of Experience Anal Sales (81.000 Residuals 1 2 2 1 4 102 3 111 13 10 11 11 13 130 Construct 16 98 16 16 12 12 4 . 1 0 FO Residuals . . . . - . . 4 - -121 10 - -12 2 10 4 14 12 o DE 12 PE 14 0 12 4 PE 10 Years of experience 10 11 Years of expert Years of experi Tears of experime 20 DO (b) Do the assumptions about the error terms seem reasonable in light of the residual plot? The plot suggests a funnel pattern in the residuals indicating that the error term assumptions appear reasonable The plot suggests a funnel pattern in the residuals indicating that the error term assumptions do not appear reasonable The plot suggests a generally horrontal band of residual points indicating that the error term assumptions do not appear reasonable. The plot suggests a generally horizontal band of residual points indicating that the error term assumptions appear reasonable The plot suggests curvature in the residuals indicating that the error term assumptions appear reasonable