US earnings data, as provided in an annual survey of Parade (here from 2005), the Sunday newspaper magazine supplementing the Sunday (or Weekend) edition of many daily newspapers in the USA.
data("Parade2005")
A data frame containing 130 observations on 5 variables.
Annual personal earnings.
Age in years.
Factor indicating gender.
Factor indicating state.
Factor. Is the individual a celebrity?
In addition to the four variables provided by Parade (earnings, age, gender, and state), a fifth variable was introduced, the “celebrity factor” (here actors, athletes, TV personalities, politicians, and CEOs are considered celebrities). The data are quite far from a simple random sample, there being substantial oversampling of celebrities.
# NOT RUN {
## data
data("Parade2005")
attach(Parade2005)
summary(Parade2005)
## bivariate visualizations
plot(density(log(earnings), bw = "SJ"), type = "l", main = "log(earnings)")
rug(log(earnings))
plot(log(earnings) ~ gender, main = "log(earnings)")
## celebrity vs. non-celebrity earnings
noncel <- subset(Parade2005, celebrity == "no")
cel <- subset(Parade2005, celebrity == "yes")
library("ineq")
plot(Lc(noncel$earnings), main = "log(earnings)")
lines(Lc(cel$earnings), lty = 2)
lines(Lc(earnings), lty = 3)
Gini(noncel$earnings)
Gini(cel$earnings)
Gini(earnings)
## detach data
detach(Parade2005)
# }
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