R Markdown

1. Chi-Square Test: Work Accident vs Left

## 
##  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

#P-value interpretation: The p-value is very small, therefore the probability of these results being random is very small.

#Chi-square test interpretation: There is a dependence between whether an employee had a work accident and whether they left the company.

#Non-technical interpretation: Employees that had work accidents are more likely to stay

2. Chi-Square Test: Promotion in Last 5 Years vs Left

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  hr$left and hr$promotion_last_5years
## X-squared = 56.262, df = 1, p-value = 6.344e-14

P-value interpretation: The p-value is very small, therefore the probability of these results being random is very small.

Chi-square test interpretation: There is a dependence between whether an employee was promoted in the last 5 years and whether they left the company.

Non-technical interpretation: Employees who were not promoted are more likely to leave.

3. Chi-Square Test: Salary vs Left

## 
##  Pearson's Chi-squared test
## 
## data:  hr$left and hr$salary
## X-squared = 381.23, df = 2, p-value < 2.2e-16

P-value interpretation: The p-value is very small, therefore the probability of these results being random is very small.

Chi-square test interpretation: There is a dependence between salary level and whether an employee left the company.

Non-technical interpretation: Employees with low salaries are more likely to leave

4. Chi-Square Test: Department vs Left

## 
##  Pearson's Chi-squared test
## 
## data:  hr$left and hr$Department
## X-squared = 86.825, df = 9, p-value = 7.042e-15

P-value interpretation: The p-value is very small, therefore the probability of these results being random is very small.

Chi-square test interpretation: There is a dependence between department and employee attrition.

Non-technical interpretation: Attrition rates vary by department