Description Usage Format Details Source Examples

Election results for the 2008 U.S. Presidential race

1 |

A data frame with 51 observations on the following 7 variables.

- state
State name abbreviation

- state_full
Full state name

- n_obama
Number of votes for Barack Obama

- p_obama
Proportion of votes for Barack Obama

- n_mc_cain
Number of votes for John McCain

- p_mc_cain
Proportion of votes for John McCain

- el_votes
Number of electoral votes for a state

In Nebraska, 4 electoral votes went to McCain and 1 to Obama. Otherwise the electoral votes were a winner-take-all.

Presidential Election of 2008, Electoral and Popular Vote Summary, retrieved 2011-04-21.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ```
#===> Obtain 2010 US House Election Data <===#
hr <- table(houserace10[,c("abbr", "party1")])
nr <- apply(hr, 1, sum)
#===> Obtain 2008 President Election Data <===#
pr <- prrace08[prrace08$state != "DC",c("state", "p_obama")]
hr <- hr[as.character(pr$state),]
(fit <- glm(hr ~ pr$p_obama, family=binomial))
#===> Visualizing Binomial outcomes <===#
x <- pr$p_obama[pr$state != "DC"]
nr <- apply(hr, 1, sum)
plot(x, hr[,"Democrat"]/nr, pch=19, cex=sqrt(nr), col="#22558844",
xlim=c(20, 80), ylim=c(0, 1), xlab="Percent vote for Obama in 2008",
ylab="Probability of Democrat winning House seat")
#===> Logistic Regression <===#
x1 <- pr$p_obama[match(houserace10$abbr, pr$state)]
y1 <- (houserace10$party1 == "Democrat")+0
g <- glm(y1 ~ x1, family=binomial)
X <- seq(0, 100, 0.1)
lo <- -5.6079 + 0.1009*X
p <- exp(lo)/(1+exp(lo))
lines(X, p)
abline(h=0:1, lty=2, col="#888888")
``` |

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