1. Chi-square test: Employee attrition vs. Work Accident
##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: table1
## X-squared = 357.56, df = 1, p-value < 2.2e-16
Technical interpretation:
The p-value is < 0.05, so there’s a significant relationship
between work accident and employee attrition.
Non-technical:
Employees who had work accidents are less likely to leave the
company.
2. Chi-Square Test: Salary vs Left
##
## Pearson's Chi-squared test
##
## data: table4
## X-squared = 381.23, df = 2, p-value < 2.2e-16
Technical:
Employees with low salaries are more likely to leave the
company.
3. Chi-square test: Employee attrition vs. Department
##
## Pearson's Chi-squared test
##
## data: table3
## X-squared = 86.825, df = 9, p-value = 7.042e-15
Technical:
A small p-value < 0.05 indicates a statistically significant
relationship between an employee’s department and whether or not they
left the company.
Non-technical:
Some departments have higher employee turnover than others.
4. Chi-square test: Employee attrition vs. Salary
##
## Pearson's Chi-squared test
##
## data: hr$left and hr$salary
## X-squared = 381.23, df = 2, p-value < 2.2e-16
Technical:
P-value < 0.05 suggests a relationship between salary levels and
employee attrition.
Non-technical:
Employees with higher salaries are less likely to leave the
company.