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 these data is y = 80 + 4x. Salesperson Years of Annual Sales Experience ($1,000s) 1 1 80 2 3 97 3 4 97 4 4 102 5 6 103 6 101 7 10 119 8 10 118 9 11 127 10 13 136 (a) Compute the residuals. Years of Annual Sales Experience ($1,000s) Residuals 1 80 97 X 3 97 4 97 4 102 6 103 8 101 10 119 10 118 11 12716 16 Residuals Residuals -4 -8 -8 -12 -12 -16 -16 2 4 6 8 10 12 14 2 4 6 8 10 12 14 O Years of Experience Years of Experience 16 16 T 12 12 + 8 Residuals Residuals -4 -8 -12 -12 - -16 -16 2 4 6 8 10 12 14 0 2 4 6 8 10 12 14 O Years of Experience Years of Experience (b) Do the assumptions about the error terms seem reasonable in light of the residual plot? O The plot suggests a funnel pattern in the residuals indicating that the error term assumptions do not appear reasonable. O The plot suggests curvature in the residuals indicating that the error term assumptions appear reasonable. O The plot suggests a funnel pattern in the residuals indicating that the error term assumptions appear reasonable. O The plot suggests a generally horizontal band of residual points indicating that the error term assumptions appear reasonable. O The plot suggests a generally horizontal band of residual points indicating that the error term assumptions do not appear reasonable