Slide showing:
Bold header: What is the mean age and salary for CEOs in each sector?
R commands and output:
> tapply(CEOs$Age, CEOs$Sector, mean)
Financial services Manufacturing Retail
51.06667 54.30000 49.54167
> tapply(CEOs$Salary, CEOs$Sector, mean)
Financial services Manufacturing Retail
5.192667 4.236000 3.160417
Another bold header: An alternative, computing mean and standard deviation in one go:
R command and its output:
> numSummary(CEOs$Salary, groups=CEOs$Sector, statistics=c("mean", "sd"))
mean sd n
Financial services 5.192667 2.361245 15
Manufacturing 4.236000 2.157409 20
Retail 3.160417 1.821692 24
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