Derive job hop index
A job hopper is a person who switches jobs frequently for financial or career advancement opportunities. In some industries, recruiters and hiring managers may perceive job hoppers in a negative light and think they are unstable or disloyal employees.
In this exercise, you will derive job hop index as:
$$\text{Job Hop Index} = \frac{\text{Total experience}}{\text{Number of companies worked}}$$
Total experience (total_experience) and the number of companies worked (no_companies_worked) are available in org_final.
Using this index, loyal employees get a high score, and job-hoppers get a low score.
Este exercício faz parte do curso
HR Analytics: Predicting Employee Churn in R
Instruções do exercício
- Derive job hop index (
job_hop_index) using the above formula. - Generate a box plot to visualize the job hop index for
ActiveandInactiveemployees.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# Add job_hop_index
emp_jhi <- emp_age_diff %>%
mutate(job_hop_index = ___ / ___)
# Compare job hopping index of Active and Inactive employees
ggplot(emp_jhi, aes(x = ___, y = ___)) +
geom_boxplot()