#--------------------------------------
#  Project: Election 2016
#--------------------------------------

mydata = read.table("http://faculty.chicagobooth.edu/nicholas.polson/teaching/41000/election2016.txt",header=T)

attach(mydata)
head(mydata)

# Correlation table

cor(cbind(G,P,Z))

###################
# Model 1
################### 
model1 = lm(VP~G+P+Z)
summary(model1)

plot(model1,labels.id=President)


###################
# Model 2
################### 
# G:I fits the model with G+I and the interaction G*I
model2 = lm(VP~G:I+P:I+Z:I+DPER+DUR+I+WAR)
summary(model2)

# Diagnostics and Model Selection
plot(model2,labels.id=President)

###################
# Prediction
################### 

# construct the new X
newdata = data.frame(cbind(G=3.03,P=1.33,Z=3))

# predict with the first model  (level = 0.95)
pred = predict.lm(model1,newdata,interval="prediction",level=0.95)