t-test One
##
## Welch Two Sample t-test
##
## data: hr1$average_montly_hours by hr1$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
p-value interpretation: Given the small p-value there is a
significant difference in means.
t-test interpretation: People that left worked significantly more
hours on average, at least 6 more hours (3% more). For retention, the
company can simply have people that work more hours reduce their hours
by 3%.
non-technical interpretation: People that leave work a little more
hours than those who don’t.
t-test Two
##
## Welch Two Sample t-test
##
## data: hr1$number_project by hr1$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
p-value interpretation: The p-value is too large for the dataset. It
means there’s no significance.
t-test interpretation: The delta between the means in both groups is
very small at 0.069. Based on all data from the t-test it’s very likely
that there’s no relation between the number of projects and whether they
left.
non-technical interpretation: More projects doesn’t make people
leave more often.
t-test Three
##
## Welch Two Sample t-test
##
## data: hr1$satisfaction_level by hr1$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
p-value interpretation: Given the small p-value there is a
significant difference in means.
t-test interpretation: The delta between both means is quite large
at 0.227. People who are less satisfied are more likely to leave than
someone who isn’t.
non-technical interpretation: Dissatisfied people are more likely to
leave the company.
t-test Four
##
## Welch Two Sample t-test
##
## data: hr1$time_spend_company by hr1$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
p-value interpretation: Given the small p-value there is a
significant difference in means.
t-test interpretation: There’s quite a large delta between the
numbers at 0.496 which is quite significant. It appears that people tend
to leave the company more late into their job rather than early on.
non-technical interpretation: More people tend to quit later on than
early on