Please help me with question 4~9

The proportion of variance in y explained by The model containing x1 and X4 is {3. a. 0.355: O h. Dion. O o. M495. (3 10.8533. 0 e. 0.25115. Regression data consisting of =200 cases were collected. The response variable is y and there were four independent variables: x1, x2, x3 and x4. The output below shows various information obtained from these data in an R session. Use this information to answer questions 4-9. p fit=lm(y~x1+x2+x3+x4) > fit12=lm(y~x1+x2) fit23=lm(y~x2+x3) > fit14=lm(y~x1+x4) > summary (fit) Call: Im ( formula = y ~ x1 + x2 + x3 + x4) Residuals: Min 10 Median 30 Max -49. 396 -13. 384 -1. 188 11.823 54.457 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 8. 71778 19. 08414 0. 457 0. 648 x1 5. 23047 0. 30209 17 . 314 anova (fit) Analysis of Variance TableResponse: y Of Sum Sq Mean Sq F value Pr(>F) x1 1 435690 435690 1013.9356 summary (fit12)| Call: Im ( formula = y ~ x1 + x2) Residuals : Min 10 Median 30 Max -53. 090 -11.848 -1. 162 12. 081 56. 250 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 11.9296 18.9933 0. 628 0. 531 x1 5. 1922 0. 1571 33. 056 anova (fit12) Analysis of Variance Table Response: y Of Sum Sq Mean Sq F value Pr ( >F) x1 1 435690 435690 1010.9