Following output is for the multiple linear regression model with employment data using education level (X1), tenure in current employment (X2), and age (X3) to estimate annual income (Y). SUMMARY OUTPUT Regression Statistics Multiple R 0.819 R.Square 0.670 0.608 Adjusted R Square Standard Error 32446.874 Observations 20 ANOVA df F Regression Residual SS MS Significance F 3 34218155395 11406051798 10.83401924 0.000393507 16 16844794605 1052799663 19 51062950000 Total t Stat p-value -3.594 0.002 Coefficients Standard Error -143,481.192 39.925.595 10.011.921 2,570,585 -2.193.884 2.158.829 2,689.241 986.353 3.895 Intercept Education (No. of years) Length of tenure in employment (yrs) Age (No. of years) 0.001 - 1.016 0.325 2.726 0.015 Which independent variables are significant at 2% significance level? Select one: O a. Length of tenure in employment only O b. more than one independent variables W O c. Age only O d. Education only In the backward elimination method of model building, Which independent variable should be deleted first using 5% significance level? Select one: O a. Length of tenure in employment only O b. Age only O c. Education only O d. more than one independent variables