Hi, I am stuck with an assignment question:

Fit a logistic regression model to predict 10 year probability of heart disease given cigarettes per day, sex, age, and education. *Summarize the association between smoking and heart disease using your model. For example, report the difference in predicted probability of heart disease in smokers and non-smokers at several levels of sex, age, and education.* Assess model fit with a binned residual plot and a calibration plot. Also report the discrimination of your model as summarized by AUC

I fit a model using the following code:

#fit model to predict 10 year probability of heart disease given cigarettes per day, sex, age, and education

model <- glm(as.factor(TenYearCHD) ~ as.factor(currentSmoker) + as.factor(male) + age + as.factor(education), data = Framingham, family = binomial)

summary(model)

and the output was shown in the snapshot

Can someone help me understand what summary is asking for and how to run binned residual plot and calibration plot?

Thank you