# This sample program is a prelim analysis of weight and height
# data
t<-matrix(scan("hawn.txt"),ncol=3,byrow=T)
hawn <-data.frame(gender=as.factor(t[,1]),height=t[,2],weight=t[,3])
# Input gender, height and weight and declare gender as factor
attach(hawn)
# Numerical Summary
summary(hawn)
# Graphical Displays
par(mfrow=c(2,2));    # Setup the graphical device

hist(height); boxplot(height); qqnorm(height);
plot(density(height));
stem(height);

hist(weight); boxplot(weight); qqnorm(weight);
plot(density(weight));
stem(weight);

plot(height,weight,main="Weight (Y) vs Height (X)")
windows()
coplot(weight~height|gender)

par(mfrow=c(2,2));
m1<-lm(weight~height)
m2<-lm(height~weight)
a0<-m2$coef[1];a1<-m2$coef[2];
p0<--a0/a1; p1<-1/a1;
plot.lm(m1)
plot.lm(m2)

windows()
par(mfrow=c(2,2));
plot(height,weight,main="I"); abline(m1$coef)
plot(weight,height,main="II"); abline(m2$coef)
plot(height,weight,main="III"); abline(c(p0,p1))

# Question:
# a. Could you construct the missing Figure IV?
# b. What's the difference between I vs. III?
# c. What's the difference between II vs. IV?
# d. Which one of the figure is more appropriate to
#    summarize the relation between weight and height? Explain.