Test 1: Left and Salary

## 
##  Pearson's Chi-squared test
## 
## data:  salary_table
## X-squared = 381.23, df = 2, p-value < 2.2e-16

P Value Interpretation: The p-value is very small (<2.2×10^−16),therefore the probability of these results being random is extremely small.

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

Non-Technical Interpretation: Employees with lower salaries are more likely to leave the company compared to those with higher salaries.

Test 2: Left and Promotion History

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

P Value Interpretation: The p-value is very small (6.344x10^-14), therefore the probability of these results being random is extremely small.

Chi-square test interpretation: There is a dependence between receiving a promotion in the last five years and whether an employee left the company.

Non-Technical Interpretation: Employees who did not receive a promotion in the last five years are significantly more likely to leave the company compared to those who were promoted.

Test 3: Left and Work Accident

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  accident_table
## X-squared = 357.56, df = 1, p-value < 2.2e-16

P Value Interpretation: The p-value is very small (2.2x10^-16), therefore the probability of these results being random is extremely small.

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

Non-Technical Interpretation: Employees who experienced a work accident are significantly less likely to leave the company compared to those who did not.

Test 4: Left and Department

## 
##  Pearson's Chi-squared test
## 
## data:  department_table
## X-squared = 86.825, df = 9, p-value = 7.042e-15

P Value Interpretation: The p-value is very small (7.042x10^-15), therefore the probability of these results being random is extremely small.

Chi-square test interpretation: There is a dependence between the department an employee works in and whether they left the company.

Non-Technical Interpretation: The results show that employees in the Management department are much less likely to leave the company compared to other departments. This suggests that management employees are generally more satisfied or engaged, and it may be beneficial for the company to study what factors contribute to their retention and apply similar strategies in other departments.