# Simple Probs

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Somebody said me that it’d be really nice to see a posting with simple simulations for the runoff this weekend. Answering such a call, this is the best I could come up with. The following is a highly simplified simulation that does not account for time trends nor for house effects. But it’s still theoretically sound as it takes a vector of polls, instead of single polls individually.

# collect some of the latest polls dilma <- c(53,54, 52,46.7,52, 50.5, 43.6) # Set the estimated percent for Dilma # based on the average of several national polls propDilma = mean(dilma) # Set the standard deviation # this measures the variability between the different polls. sdDilma = sd(dilma) # Function to simulate a single election simElection <- function(prop,sd){ return(rnorm(1,mean=prop,sd=sd)) } # Simulate the percent Dilma in 1000 elections simPropDilma = replicate(1000, simElection(propDilma,sdDilma)) # Calculate the percent of times Dilma wins perDilmaWin = mean(simPropDilma > 50) perDilmaWin [1] 0.517 hist(simPropDilma, freq=FALSE, xlab="Popular Vote", main="Distribution of Dilma's Popular Vote", col="red", xlim=c(30,70), ylim=c(0, .15) ) curve(dnorm(x, mean=mean(simPropDilma), sd=sd(simPropDilma)), add=TRUE, col="blue", lwd=2)

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