##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: hr$Work_accident and hr$left
## X-squared = 357.56, df = 1, p-value < 2.2e-16Technical Interpretation:
The p-value is less than 0.05, indicating a statistically significant
relationship between work accidents and employee attrition.
Non-Technical Interpretation:
Employees who had work accidents are less likely to leave the
company.
##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: hr$promotion_last_5years and hr$left
## X-squared = 56.262, df = 1, p-value = 6.344e-14Technical Interpretation:
The p-value is less than 0.05, meaning there is a significant
relationship between promotions and employee attrition.
Non-Technical Interpretation:
Employees who were promoted are much more likely to stay at the
company.
##
## Pearson's Chi-squared test
##
## data: hr$salary and hr$left
## X-squared = 381.23, df = 2, p-value < 2.2e-16Technical Interpretation:
The p-value is less than 0.05, showing a statistically significant
relationship between salary level and employee attrition.
Non-Technical Interpretation:
Employees with higher salaries are less likely to leave the company.
##
## Pearson's Chi-squared test
##
## data: hr$Department and hr$left
## X-squared = 86.825, df = 9, p-value = 7.042e-15Technical Interpretation:
The p-value is less than 0.05, indicating that there is a significant
relationship between department and employee attrition.
Non-Technical Interpretation:
Some departments have much higher employee turnover than others.