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.

This exercise is part of the course

HR Analytics: Predicting Employee Churn in R

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Exercise instructions

Derive job hop index (job_hop_index) using the above formula.
Generate a box plot to visualize the job hop index for Active and Inactive employees.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# 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()

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