Chi square test assignment

First Chi-sqaure test

## 
##  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 is small, therefore significant
• technical explanation: there is an association between having work accident and leaving
• non- technical explanation: employees that had work accidents are more likley to leave

Second Chi-square test

chi-square test

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

• P value is small, therefore it is significant
• Technical Interpretation : there is a significant relationship between employee’s
• department and whether they left the company
• Non-Technical Interpretation : HR staff more likely to leave the company compared
• to other departments

Third Chi-square test

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

• P Value is very small, therefore is significant
• Technical Interpretation : there is a significant relationship between employee’s promotion in last 5 years and whether they left the company
• Non-Technical Interpretation : Employees who received a promotion are more likely to stay.

Fourth Chi-square test

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

• P value is small, therefore is significant
• Technical Interpretation : There is a significant relationship between employees who left and salary
• Non-Technical Interpretation : Employees with low salaries are more likely to leave