Build your first logistic regression model

In the video, we build a simple logistic regression model by using emp_age to predict turnover. In this exercise, you will build a similar model to predict turnover using percent_hike.

Also, as discussed in the video, we dropped the following columns from the dataset:

emp_id, mgr_id
date_of_joining, last_working_date, cutoff_date
mgr_age, emp_age
median_compensation,department
status

This new dataset is available in train_set_multi.

Este ejercicio forma parte del curso

HR Analytics: Predicting Employee Churn in R

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Instrucciones del ejercicio

Build a simple logistic regression model to predict turnover using percent_hike.
Print the summary of this model.

Ejercicio interactivo práctico

Prueba este ejercicio y completa el código de muestra.

# Build a simple logistic regression model
simple_log <- ___(___, 
                  family = "binomial", data = train_set_multi)

# Print summary
___(simple_log)

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