1: T-test of Average Monthly Hours by Left
##
## Welch Two Sample t-test
##
## data: hr1$average_montly_hours by hr1$Employee_Status
## t = 7.5323, df = 4875.1, p-value = 5.907e-14
## alternative hypothesis: true difference in means between group Left and group Stayed is not equal to 0
## 95 percent confidence interval:
## 6.183384 10.534631
## sample estimates:
## mean in group Left mean in group Stayed
## 207.4192 199.0602
P-value: The very low p-value (< 2.2e-16) means the difference is
significant
T-test interpretation: The difference in average monthly hours
between employees who left and those who stayed is statistically
significant (t = 7.53, p < 0.001).
Non-technical interpretation:Employees who left worked more hours
per month than those who stayed.
2: T-test of Satisfaction Levels
##
## Welch Two Sample t-test
##
## data: hr1$satisfaction_level by hr1$Employee_Status
## t = -46.636, df = 5167, p-value < 2.2e-16
## alternative hypothesis: true difference in means between group Left and group Stayed is not equal to 0
## 95 percent confidence interval:
## -0.2362417 -0.2171815
## sample estimates:
## mean in group Left mean in group Stayed
## 0.4400980 0.6668096
P-value: The very low p-value (< 2.2e-16) means the difference is
significant.
T-test interpretation: The t-test shows a significant difference in
satisfaction levels between employees who left and those who stayed,
where the difference in satisfaction level is at least 0.22.
Non-technical interpretation:Employees who left had significantly
lower satisfaction levels than those who stayed.
3: T-test of Last Evaluation
##
## Welch Two Sample t-test
##
## data: hr1$last_evaluation by hr1$Employee_Status
## t = 0.72534, df = 5154.9, p-value = 0.4683
## alternative hypothesis: true difference in means between group Left and group Stayed is not equal to 0
## 95 percent confidence interval:
## -0.004493874 0.009772224
## sample estimates:
## mean in group Left mean in group Stayed
## 0.7181126 0.7154734
P-value: The high p-value (0.4683) means the difference in last
evaluation scores is likely due to chance
T-test interpretation: The t-test shows no significant difference in
last evaluation scores between employees who left and those who stayed,
as the confidence interval [-0.0045, 0.0098] includes zero.
Non-technical interpretation: Employees who left and those who
stayed had similar last evaluation scores, with no meaningful
difference.
4: T-test of Number of Projects
##
## Welch Two Sample t-test
##
## data: hr1$number_project by hr1$Employee_Status
## t = 2.1663, df = 4236.5, p-value = 0.03034
## alternative hypothesis: true difference in means between group Left and group Stayed is not equal to 0
## 95 percent confidence interval:
## 0.006540119 0.131136535
## sample estimates:
## mean in group Left mean in group Stayed
## 3.855503 3.786664
P-value: The p-value (0.03034) is low, indicating the difference is
unlikely
T-test interpretation: The t-test shows a significant difference in
the number of projects between employees who left and those who stayed,
where the difference is at least 0.007
Non-technical interpretation:Employees who left worked on slightly
more projects than those who stayed.