################################################
# WLoss1 Example -- Source code file wloss1.r #
################################################

loss = c(8.5, 11.6, 10.2, 10.9, 9.0, 
         9.6, 9.9, 11.3, 10.5, 11.2,
         8.7, 9.3, 8.2, 8.3, 9.0,  
         9.4, 9.2, 12.2, 8.5, 9.9)
center = c(rep('C', 10), rep('D', 10))
wloss = data.frame(center=center, loss=loss)
cat("wloss data frame:\n")
print(wloss)

model1 = aov(loss ~ center, data=wloss)
cat("Classical ANOVA summary:\n")
print(summary(model1))

# Create vector of dummy values
dummy = rep(0, 20)
dummy[center == 'C'] = 1
cat("Vector of dummy values:\n")
print(dummy)

# Create data frame named with_dummy
with_dummy = data.frame(dummy=dummy, loss=loss)
cat("with_summy data frame\n")
print(with_dummy)

model2 = lm(loss ~ dummy, data=with_dummy)
cat("Regression model with dummy variable\n")
print(summary(model2))

p = fitted(model2)
r = residuals(model2)

pdf(wloss1.pdf)
	
# Residual Plot
plot(p, r, main="Residual Plot for Model with Dummy Variables",
           xlab="Predicted Values",
           ylab="Residuals")
abline(h=0, lty="dashed")
     
# Normal Plot
qqnorm(r, main="Normal Plot", ylab="Residuals") 

dev.off( )