Please help me to answer what is asked based on the two photos attached. Thank you.

\f34 59 24.71735 mi 70.14223 0.13647 71.042 0.29730 35 39 23.00032 smoking 0.93432 0.56176 1.663 0.09627 . 36 73 27.21902 exercise 0.56244 0.60455 1.427 0.15370 37 54 27.30000 fruit -2.04587 0.85857 -2.354 0.01712 ' 38 73 24.39085 veg 0.04720 0.23051 0.205 0.83782 39 53 21.23835 ___ 40 54 25.66604 Signif. codes: a new 0.001 m 0.01 w 0.05 >.' 0.1 ' . 1 41 61 26.67673 42 44 26.35095 (Dispersion parameter for binomial family taken to be 1) 43 51 27.30000 44 56 23.81833 Null deviance: 70.227 on 54 degrees of freedom 45 74 26.30000 Residual deViance: 35.359 on 57 degrees of freedom 45 59 29.77090 (1 observation deleted due to missingness) 47 75 25.80797 AIC: 51.559 45 40 21.97185 49 54 10.80682 Number of Fisher Scoring iterations: 7 50 40 28.58292 51 53 27.30000 52 62 23.41161 53 45 23.47300 54 75 23.84975 55 55 27.86860 55 70 17-09625 Diagnostic Checking 57 55 20.15055 58 60 15-94070 1. Cheek the linearity of the predictors. 59 73 12-20105 2. Display the top 5 largeest values of inuential variables 60 59 19-93989 3. Check the multicollinenrity 51 55 24.78464 62 60 25.09199 63 70 21.93329 64 55 27.30000 65 69 27.36574 66 46 25.94592 . Discuss the predictors that are signicant to the model. . Interpret each coefcient of the predictors. . Using the model, show an example at predicting whether a person has cancer or no cancer. Logistic Regression full: g1m(cancer-., binomial, . . cancer) summuy(fu11) Call: g1m|zl) (Intercept) 77.56811 3.96164 71.910 0.05609 . age 0.11751 0.04407 2.619 0.00552 u gender 2.57370 1.17685 2.157 0.02875 1