Load the dataset

Perform t-tests 1

## 
##  Welch Two Sample t-test
## 
## data:  hr$satisfaction_level by hr$left
## t = 46.636, df = 5167, p-value < 2.2e-16
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
##  0.2171815 0.2362417
## sample estimates:
## mean in group 0 mean in group 1 
##       0.6668096       0.4400980

Techincal Interpretation 1

t(5167) = 46.636, p < 2.2e-16

95% Confidence Interval: (0.2172, 0.2362)

Mean Satisfaction: Stayed (0.667), Left (0.440)

Since p < 0.05, the difference is statistically significant. Employees who left had significantly lower satisfaction levels than those who stayed.

Non-Technical Interpretation1

Employees who quit were much less satisfied at work than those who stayed. This suggests that dissatisfaction may be a key reason for employees leaving.

Create and Display Plots 1

Perform t-tests 2

## 
##  Welch Two Sample t-test
## 
## data:  hr$last_evaluation by hr$left
## t = -0.72534, df = 5154.9, p-value = 0.4683
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
##  -0.009772224  0.004493874
## sample estimates:
## mean in group 0 mean in group 1 
##       0.7154734       0.7181126

Technical Interpretation 2

t(5155) = -0.725, p = 0.4683

95% Confidence Interval: (-0.0098, 0.0045)

Mean Last Evaluation: Stayed (0.715), Left (0.718)

Since p > 0.05, the difference is not statistically significant. There is no strong evidence that last evaluation scores differ between those who stayed and left.

Non-Technical Interpretation 2

Performance evaluations do not seem to impact whether an employee stays or leaves. Employees who quit had similar evaluations to those who remained.

Create and Display Plots 2

Perform t-tests 3

## 
##  Welch Two Sample t-test
## 
## data:  hr$average_montly_hours by hr$left
## t = -7.5323, df = 4875.1, p-value = 5.907e-14
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
##  -10.534631  -6.183384
## sample estimates:
## mean in group 0 mean in group 1 
##        199.0602        207.4192

Technical Interpretation 3

t(4875) = -7.5323, p = 5.91e-14

95% Confidence Interval: (-10.53, -6.18)

Mean Monthly Hours: Stayed (199.06), Left (207.42)

Since p < 0.05, the difference is statistically significant. Employees who left worked more hours on average than those who stayed.

Non-Technical Interpretation 3

Employees who quit were working longer hours compared to those who stayed. Overwork might be a factor in employee attrition.

Create and Display Plots 3

Perform t-tests 4

## 
##  Welch Two Sample t-test
## 
## data:  hr$time_spend_company by hr$left
## t = -22.631, df = 9625.6, p-value < 2.2e-16
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
##  -0.5394767 -0.4534706
## sample estimates:
## mean in group 0 mean in group 1 
##        3.380032        3.876505

Technical Interpretation 4

t(9626) = -22.631, p < 2.2e-16

95% Confidence Interval: (-0.5395, -0.4535)

Mean Time at Company: Stayed (3.38 years), Left (3.88 years)

Since p < 0.05, the difference is statistically significant. Employees who left had spent more time at the company than those who stayed.

Non-Technical Interpreation 4

Employees who left had been at the company longer on average. This may indicate that after a few years, employees are more likely to leave.

Create and Display Plots 4