#	Wolfgang Peter
# ------------------------------------------------------------------------------
# Erstellung der Kreuztabelle
my.table <- matrix(c(6,14,21,11),2,2) 
# Labels
dimnames(my.table)<- list(
  Sex=c("Frauen","Männer" )
  ,Fusball=c("Ja","Nein" ))

# Ausgabe der Tabelle
my.table   
# Anteil in der Gruppe Geschlecht in Prozent
round(prop.table(my.table, 1), digits=2) *100
# Chi-Test 
chisq.test(my.table)
# Resudien
residuals<-chisq.test(my.table)$residuals
#   Phi-Koeffizient als Maß für den Zusammenhang
Chi<-chisq.test(my.table,correct=F)
phi<-round(sqrt(Chi$statistic/sum(Chi$observed)), digits=2)
names(phi)<-"Phi-Koeffizient"
phi  

# PLOT
# ---- 
par(mfrow=c(2, 2))
color<-c(4,2)
prozent<-prop.table(my.table)

# Barplot   beside => gruppiert
barplot(t(prozent)
    ,horiz = F, beside = T
    ,axes=F, col=color
    ,main="Gruppiertes Balkendiagramm")
par(las=1)
axis(2,at = c(0,0.2,.4,0.6,.8), labels = c("0","20%","40%","60%",""))
  
color<-c(3,4) 
mosaicplot(my.table,color=color
    ,main="Mosaicplot",sub=NA
    ,type = "pearson" )

# Gruppiert Balkendiagramm
prozent<-prop.table(my.table,1) 
barplot(t(prozent)
    ,horiz = T, beside = F
    ,axes=F, col=color
    ,main="Anteil in den Gruppen\nFrauen/Männer") 
axis(1,at = c(0,0.50,1), labels = c("0","50%","100%"))


prozent<-  prop.table(my.table,2) 
barplot(prozent
    ,horiz = T, beside = F
    ,axes=F, col=color
    ,main="Anteil in den Gruppen\nFusball Ja/Nein")  
axis(1,at = c(0,0.50,1), labels = c("0","50%","100%"))