Please help me with my hw, explanation appreciated!

Investigators fit a logistic regression model (Model A) of death on age, education, disease count categories, and BMI The following graph shows a lowess smoother of Pearson residuals from Model A versus BMI. What is the conclusion, after adjusting for age, education, and disease categories? Lowess smoother Pearson residual N 20 30 50 60 bri bandwidth = 8 a. The independence of error terms assumption made by Model A appears to be violated. b. The odds of death are approximately 1.65 among those with the lowest BMI in the study. c. The unequal variances assumption made by Model A appears to be violated. d. The assumption of linear relationship between the log odds of death and BMI, made by Model A, appears to be violated in the low range of BMI. e. The normality of error terms assumption made by Model A appears to be violated.Investigators fit a logistic regression model (Model A) of death on age, education, disease count categories, and BMI: Stata Output Model A . logit died age education bmi i. discat Logistic regression Number of obs 562 LR chi2 (6) 56.53 Prob > chi2 0.0000 Log likelihood = -287.21623 Pseudo R2 0.0896 died | Coef. Std. Err. P> |zI [958 Conf. Interval] age I . 0723776 . 0139645 5.18 0.000 . 0450078 . 0997475 education | . 0257008 . 0279795 0.92 0.358 -. 0291381 . 0805397 bmi | - . 0508686 . 0192579 -2. 64 0.008 -. 0886135 -. 0131238 discat | 1 . 6061456 . 5718123 1.06 0.289 -. 5145859 1. 726877 1.052233 . 5813279 1. 81 0.070 -. 0871484 2.191615 w 1. 411006 . 6667187 2.12 0.034 . 1042617 2. 717751 cons 1 -6.326839 1.500227 -4.22 0.000 -9.267231 -3.386448