# Example 2.9, Voting Outcomes and Campaign Expenditures
# Data set: vote1
load("vote1.Rdata")
# Recap the estimated model
model=lm(voteA~shareA, data=data)
cat("The example uses the data set of voting outcomes and expenditures that was used in Example 2.5.\nIn the previous example, we estimated the model voteA = beta0 + beta1 * shareA + u, where voteA is ",
paste(desc[desc[,1]=="voteA",2]), ", and shareA is ", paste(desc[desc[,1]=="shareA",2]),
"\nThe estimated regression line was\nvoteAhat = ", round(model$coefficients[1],digits=2), " + ",
round(model$coefficients[2],digits=3), " * shareA\n",
"n = ", nrow(data), ", R^2 = ", round(summary(model)$r.squared,digits=3), sep="")
# Interpretation of R^2
cat("The value of R^2 indicates that ", 100*round(summary(model)$r.squared,digits=3),
"% of the variation in salary is explained by roe, which is a sizable portion",
sep="")