# Olympic Example
# Use a quadratic regression model to
# fit the olympic.txt dataset;

# Load data frame from disk 
olympic <- read.table("c:/datasets/olympic.txt", header=TRUE)

# Show output and plots for simple linear model.
model1 <- lm(chol ~ fat, data=olympic)
cat("Summary for Simple Linear Model (model1)\n")
print(summary(model1))

# Send graphs to output file.
pdf("c:/datasets/olympic-graphs.pdf")

p = predict(model1)
r = resid(model1)
plot(p, r, main="Olympic Example -- Residual Plot", 
   sub="Simple Regression Model (model1)",
   xlab="Predicted Value", ylab="Residual")
abline(h=0, lty="dashed", col="red")
qqnorm(r, main="Olympic Example -- Normal Plot", 
   sub="Simple Regression Model (model1)")
qqline(r)

# Show output and plots for quadratic linear model.
fatsq <- olympic$fat ^ 2
model2 <- lm(chol ~ fat + fatsq, data=olympic)
cat("Summary for Quadratic Model (model2)\n")
print(summary(model2))

p = predict(model2)
r = resid(model2)
plot(p, r, main="Olympic Example -- Residual Plot", 
   sub="Quadratic Model (model2)",
   xlab="Predicted Value", ylab="Residual")
abline(h=0, lty="dashed", col="red")
qqnorm(r, main="Olympic Example -- Normal Plot", 
   sub="Quadratic Regression Model (model2)")
qqline(r)

dev.off( )