Election results for the 2008 U.S. Presidential race

Usage

prrace08

Format

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

Source

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

Details

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

Examples


# ===> 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$p_obama, family = binomial))
#> 
#> Call:  glm(formula = hr ~ pr$p_obama, family = binomial)
#> 
#> Coefficients:
#> (Intercept)   pr$p_obama  
#>      -5.726        0.103  
#> 
#> Degrees of Freedom: 49 Total (i.e. Null);  48 Residual
#> Null Deviance:	    107.4 
#> Residual Deviance: 48.72 	AIC: 138.7

# ===> 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")