Examining & interpreting logistic regression outputs

In the previous exercise, you fit a logistic regression, bus_out. During this exercise, you will examine bus_out and interpret the results of the regression using the tools you learned about in Chapter 1:

print() includes the coefficient estimates (i.e., slopes and intercepts) for different predictor variables and information about the model fit such as deviance.
summary() includes the print() outputs as well as standard errors, z-scores, and P-values for the coefficient estimates.
tidy() includes the summary() coefficient table as a tidy data frame.

Recall that regression coefficients can help us understand both the direction of relationships and statistical significance of coefficients. For logistic regression, a positive coefficient indicates that the probability of an event occurring increases as a predictor increases.

Print the model's output using print().

Exercise

Examining & interpreting logistic regression outputs

Instructions 1/4