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## Pearson's Chi-squared test with Yates' continuity correction
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## data: hr$left and hr$Work_accident
## X-squared = 357.56, df = 1, p-value < 2.2e-16There is an association between leaving and work accidents, Where employees without accidents are more likely to leave
Employees without work accidents are more than three times more likely to leave (0.265 / 0.078)
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## Pearson's Chi-squared test with Yates' continuity correction
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## data: hr$left and hr$promotion_last_5years
## X-squared = 56.262, df = 1, p-value = 6.344e-14There is a statistically significant association between promotions and employee turnover (p < 0.05), indicating that promotion history affects the likelihood of leaving.
Employees who were not promoted in the last 5 years are more likely to leave than those who were promoted.
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## Pearson's Chi-squared test
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## data: hr$left and hr$salary
## X-squared = 381.23, df = 2, p-value < 2.2e-16There is a statistically significant association between salary level and employee turnover (p < 0.05), which suggests that the likelihood of leaving the company is related to how much employees are paid.
Employees with low salaries are much more likely to leave the company than those with medium or high salaries.
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## Pearson's Chi-squared test
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## data: hr$left and hr$number_project
## X-squared = 5373.6, df = 5, p-value < 2.2e-16The p-value is significant (p < 0.05), indicating that the number of projects is associated with employee turnover. In other words, the number of projects an employee is involved in impacts the likelihood of leaving.
Employees working on either very few or too many projects are more likely to leave the company.