This activity requires that you look at data from the class for gender
and preferred lifetime acheivement (which we've abbreviated as
PLA. In R, you can read in the complete set of
data for our classes with
GP = read.csv("/home/rebelsky/Stats115/Data/GenderedPLAs.csv")
Activity 6-3.a asks you to determine the marginal distribution of the
preferred lifetime acheivement variable
and then to graph it.
How do you get information from that data frame, except by
counting manually? Recall that R provides a useful
summary function. We can call that function
on the whole frame.
summary(GP)
But we really care only about the PLA variable, so we can also ask for
that.
summary(GP$PLA)
And, if the purpose of our graph is our own understanding, we can just
bring up the simplest bar graph.
barplot(summary(GP$PLA))
This problem requires us to figure out the
conditional distribution. You should start by
counting a few lines by hand. However, you will soon find that
tedious.
Do we have enough R tools to figure that out? Certainly. We simply
select the rows that contain women and then the rows that contain men.
Women = GP[GP$Gender == "Female", ]
Men = GP[GP$Gender == "Male", ]
You can then fill in the table by summarizing the two parts.
summary(Women$PLA)
summary(Men$PLA)
