5. Extend the logistic regression model from the income prediction use case to include the continuous variables as well.

a. Create and examine a correlation plot for these variables. Do they exhibit multicollinearity?

b. Examine the summary statistics for the continuous variables. Do you observe any outliers? If so, address them appropriately.

c. Fit a logistic regression model to the dataset. This time, include both the continuous and categorical variables. Use the same training/test dataset split as the use case.

d. Examine the summary of the model. Were the continuous variables significant?

How does this model compare to the model without the continuous variables?

e. Generate predictions for the test dataset using a 0.50 threshold and create a confusion matrix of your results. Compare these results to the model from earlier in the chapter.