# Diverse Auswertungen von Beispiel 2.1:

dd <- read.table("StatInf2000.txt", header=T)
str(dd)


# Kuchen- und Stabdiagramm der Variable "Zufallsziffer":

t <- table(dd$RandomN)
n <- sum(t)
par(mai=c(0,0,0,0),ps=20)
pie(t)
par(mai=c(0.5,0.5,0.20,0),ps=20)
barplot(t/n,ylim=c(0,0.5),width=0.5,xlim=c(0,10),space=1)


# Analyse der Variable "Alter":

X <- dd$Age

# Empirische Verteilungsfunktion der Variable "Alter":

par(mai=c(0.5,0.5,0.05,0.05))

plot.ecdf(X,pch="*",verticals=F,lwd="2",xlab="",ylab="", main="",usr=c(19,40,0,1),yaxp=c(0,1,4)); grid(ny=4)

# Histogramme der Variable "Alter":

par(mai=c(0.5,0.5,0,0))

hist(X,breaks=seq(from=19.5,to=40.5,by=1),col="grey",xlab="",ylab="", main="",freq=F,xlim=c(19.5,40)); rug(X)

hist(X,breaks=seq(from=19.5,to=40.5,by=2),col="grey",xlab="",ylab="", main="",freq=F,xlim=c(19.5,40)); rug(X)

hist(X,breaks=seq(from=20.5,to=40.5,by=2),col="grey",xlab="",ylab="", main="",freq=F,xlim=c(19.5,40),ylim=c(0,0.25)); rug(X)


# Box-Plot und Box-Whisker-Plot der Variable "Alter":

par(mai=c(0.05,0.5,0.05,0.05))
boxplot(X,ylim=c(19,40), range=Inf, boxwex=1.5)
boxplot(X,ylim=c(19,40), range=1.5, boxwex=1.5)