Refer to the Summary Output; please answer the following questions a. How many percent of the variation in the annual income is determined by the three independent variables? (round to the nearest hundredth) (2 points) b. Given the output, one additional year of education constructs how much more in the annual income? (2 points) c. If the significance level is 0.05, which independent variable is NOT significantly related to the dependent variable, the annual income? (2 points) d. By removing all independent variables that are not significant at the 0.05 level of significance from the estimated regression equation, the estimated regression equation in this case is as follow SUMMARY OUTPUT Aggression Stotimes 0.805496367 R Squire 064RM4397 Adjusted R Square 0.607509621 Standard Error 32478-10324 Observations 20 ANOVA F Son conce F Regression 131 1087768 16565443884 15:7044149 0.600137073 Residual 17932062232 105-4827190 otal 51062950000 Conflictenti Standard Error Prolee Lower SON Elaper 15 over 93.Dippp 95.O Intercept 138671.6838 39682 26121 -1.494550954 0.00277665 -272393537 54949 -272394 54949 Education [No. of years) 9548.89333 2539.098027 3.376493917 0.00150576 4231864759 149459 423186 147459 Age (No. of years) 2234 556097 879 8847517 [9 3960069 0.02115754 378 161542 409095 378-362 4090.95 The estimated multiple linear regression equation (Y hat ) is : y = - 138671.68 + 9588.89x, + 2234.56x; What would be the value of the sum of squares due to regression (SSR) if the total sum of squares (SST) is 25.32 and the sum of squares due to error (SSE) is 6.897 (round to the nearest hundredth)