
           library(readr)
           library(AER)
           library(dplyr)
           Titanic_2 <- read_csv("https://stanford.io/2O9RUCF")[,-3]
           colnames(Titanic_2) = c("Survived", "Class", "Sex", "Age", "Siblings", "Parents", "Fare")
           Titanic_2$Class <- as.factor(Titanic_2$Class)
           passengers <- cbind("Class" = as.factor(1:3), as.data.frame(Titanic_2 %>% select(-Sex,-Survived,-Class) %>% summarise_all(funs(mean)) %>% mutate(Sex = "male")))


           # fit the Logit model and assign it to `Logit_mod`
           
           
           # obtain a robust summary of the model coefficients


           # predict the probability of survival for the three passengers


           # fit the Logit model, assign it to `Logit_mod`
           Logit_mod <- glm(Survived ~ ., 
           family = binomial(link = "logit"), 
           data = Titanic_2)
           
           # obtain a robust summary of the model coefficients
           coeftest(Logit_mod, vcovHC)
           
           # predict the probability of survival for the hypothecial individuals
           predict(Logit_mod, newdata = passengers, type = "response")


           test_predefined_objects("Titanic_2")
           test_object("Logit_mod")
           test_predefined_objects("passengers")
           test_output_contains("predict(Logit_mod, newdata = passengers, type = 'response')
")
           success_msg("Nicely done! Note that ")