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1️⃣ T-Test: Satisfaction Level by Attrition

Perform the t-test

## 
##  Welch Two Sample t-test
## 
## data:  satisfaction_level by 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

Technical Interpretation (p-value)

The p-value is extremely small (p < 0.001), which is well below the 0.01 significance level. Therefore, we reject the null hypothesis and conclude that there is a statistically significant difference in satisfaction levels between employees who left and those who stayed.

Non-Technical Interpretation

Employees who left the company tend to have significantly lower satisfaction levels than those who stayed.

Visualization

2️⃣ T-Test: Average Monthly Hours by Attrition

Perform the t-test

## 
##  Welch Two Sample t-test
## 
## data:  average_montly_hours by 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 (p-value)

The p-value is extremely small (p < 0.001), which is below the 0.01 significance level. Therefore, we reject the null hypothesis and conclude that there is a statistically significant difference in average monthly hours between employees who left and those who stayed.

Non-Technical Interpretation

Employees who left tend to work more hours than employees who stayed.

Visualization

3️⃣ T-Test: Number of Projects by Attrition

Perform the t-test

## 
##  Welch Two Sample t-test
## 
## data:  number_project by left
## t = -2.1663, df = 4236.5, p-value = 0.03034
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
##  -0.131136535 -0.006540119
## sample estimates:
## mean in group 0 mean in group 1 
##        3.786664        3.855503

Technical Interpretation (p-value)

The p-value is 0.03034, which is greater than the 0.01 significance level. Therefore, we fail to reject the null hypothesis. This means there is not enough strong evidence to conclude a statistically significant difference in the number of projects between employees who left and those who stayed.

Non-Technical Interpretation

There is no strong evidence that the number of projects is meaningfully different between employees who leave and those who stay.

Visualization

4️⃣ T-Test: Time Spent at Company by Attrition

Perform the t-test

## 
##  Welch Two Sample t-test
## 
## data:  time_spend_company by 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 (p-value)

The p-value is extremely small (p < 0.001), which is below the 0.01 significance level. Therefore, we reject the null hypothesis and conclude that there is a statistically significant difference in time spent at the company between employees who left and those who stayed.

Non-Technical Interpretation

Employees who leave tend to have spent more time at the company compared to those who stay.

Visualization