Test 1: Salary vs Left

##         
##             0    1
##   high   1155   82
##   low    5144 2172
##   medium 5129 1317
## 
##  Pearson's Chi-squared test
## 
## data:  tab1
## X-squared = 381.23, df = 2, p-value < 2.2e-16

Technical: If p-value < .05 -> there is a relationship.

Non-technical: Salary affects whether or not employees leave

Test 2: Department vs Left

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

Technical: If p-value < .05 -> there is a relationship.

Non-technical: Some departments have more employees leaving.

Test 3: Work Accident vs Left

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table(hr$Work_accident, hr$left)
## X-squared = 357.56, df = 1, p-value < 2.2e-16

Technical: If p-value < .05 -> there is a relationship.

Non-Technical: Work accidents affect if employees leave

Test 4: Promotion vs Left

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

Technical: If p-value < .05 -> there is a relationship

Non-technical: Promotions affect if employees leave.