Forecasting car sales. forecasts of automotive vehicle sales in the united states provide the basis for financial and strategic planning of large automotive corporations. the following forecasting model was developed for y, total monthly passenger car and light truck sales (in thousands): e(y)= βo+β1x1+β2x2+β3x3+β4x4+β5x5where x1= average monthly retail price of regular gasoline x2=annual percentage change in gnp per quarter x3=monthly consumer confidence index x4=total number of vehicles scrapped (millions) per month x5=vehicle seasonality the model was fitted to monthly data collected over a 12-year period (i. e., n 144 months) with the following results: ŷ= -676.42 - 1.93x1+6.54x2+2.02x3+ 0.08x4 +9.82x5r^2= 0.856durbin—watson d=1.01 (a) is there sufficient evidence to indicate that the model contributes information for the prediction of y? test using α=0.05 (b) is there sufficient evidence to indicate that the regression errors are positively correlated? test using α= 0.05 (c) comment on the validity of the inference concerning model adequacy in light of the result of part b.