#
#
# Written by:
# -- 
# John L. Weatherwax                2009-04-21
# 
# email: wax@alum.mit.edu
# 
# Please send comments and especially bug reports to the
# above email address.
# 
#-----

# fix the random.seed, so I'll always get the same answer:
set.seed(10131985)

data(Orange)
attach(Orange) 

# Lets display the data and the linear model:
#
postscript("../../WriteUp/Graphics/Chapter1/ex_1_21_plot.eps", onefile=FALSE, horizontal=FALSE)

plot( age, circumference )
m1 = lm( circumference ~ age ) # the model with only one predictor: age
abline(m1)

dev.off()

summary(m1)


# create a factor based on the specific tree:
#
TF = as.factor( Tree ) 
m2 = lm( circumference ~ age + TF ) # the model with two predictors: age and the specific tree factor
summary(m2)


# We can use the anova method to compare whether this second model (m2) is an improvement over the first model (m1):
# m1 < m2, since m2 has the additional factor term
# 
anova(m1,m2)