Question 1: Salary
##
## Pearson's Chi-squared test
##
## data: hr$left and hr$salary
## X-squared = 381.23, df = 2, p-value < 2.2e-16
Analysis:
p-value interpretation: The p-value is very small (p < 2.2e-16)
and less than alpha (0.01), indicating a significant association between
salary level and employee turnover.
Chi Square Test interpretation: There is a dependence between salary
level and employee turnover.
non-technical interpretation: Lower-paid employees are much more
likely to leave the company than higher-paid employees.
Question 3: Work Accident
##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: hr$left and hr$Work_accident
## X-squared = 357.56, df = 1, p-value < 2.2e-16
Analysis:
p-value interpretation: The p-value is very small (p < 2.2e-16)
and less than alpha (0.01), indicating a significant association between
work accidents and employee turnover.
Chi Square Test interpretation: There is a dependence between
experiencing a work accident and employee turnover.
non-technical interpretation: Employees who experienced work
accidents are less likely to leave the company than those who
didn’t.
Question 4: Department
##
## Pearson's Chi-squared test
##
## data: hr$left and hr$Department
## X-squared = 86.825, df = 9, p-value = 7.042e-15
Analysis:
p-value interpretation: The p-value is very small (p < 7.042e-15)
and less than alpha (0.01), indicating significant differences in
turnover rates across departments.
Chi Square Test interpretation: There is a dependence between
department and employee turnover.
non-technical interpretation: Management and RandD are less likely
to leave the company.