#Datensatz einlesen
bodyX <- read.table("...bodyX.txt",header=T,sep="\t",quote="")

#Oberschenkel
boxplot(bodyX$Thigh~bodyX$Gender)
t.test(bodyX$Thigh~bodyX$Gender)
table(bodyX$Gender)

#Rechnung per Hand
sdw<-sd(sw$Thigh)
sdm<-sd(sm$Thigh)
se<-(sdw^2/length(sw$Thigh)+sdm^2/length(sm$Thigh))^0.5
tmw<-(mean(sm$Thigh)-mean(sw$Thigh))/se
tmw
dfmw<-length(sw$Thigh)+length(sm$Thigh)-2
dfmw
2*pt(tmw,dfmw) #Weil t negative ist
#t und Normal Resultate sind fast gleich
2*pnorm(tmw)

#Subsets nach Geschlecht
sm<-subset(bodyX,bodyX$Gender=="M")
sw<-subset(bodyX,bodyX$Gender=="W")

#Histogramme
JavaGD(,400,600)
par(mfrow=c(2,1))
hist(sm$Thigh)
hist(sw$Thigh)
#Vergleichbar machen
hist(sm$Thigh,xlim=c(45,80),breaks=seq(45,80,5))
hist(sw$Thigh,xlim=c(45,80),breaks=seq(45,80,5))

#Elbogen
JavaGD(,400,600)
boxplot(bodyX$ElbowD~bodyX$Gender)
t.test(bodyX$ElbowD~bodyX$Gender)
#Oder
t.test(sm$ElbowD,sw$ElbowD)

#Rechnung per Hand
sdw<-sd(sw$ElbowD)
sdm<-sd(sm$ElbowD)
se<-(sdw^2/length(sw$ElbowD)+sdm^2/length(sm$ElbowD))^0.5
tmw<-(mean(sm$ElbowD)-mean(sw$ElbowD))/se
tmw
dfmw<-length(sw$ElbowD)+length(sm$ElbowD)-2
dfmw
2*pt(-tmw,dfmw) #NB Minus, um t negativ zu machen