### Presidential Election 2008 - McCain v/s Obama - Rev 1

Here is the latest update of results from a statistical simulation model to predict the outcome of the 2008 presidential election. The model accounts for the fact that the reported voter preferences are only one of many likely scenarios because of the statistical margin of error inherent in all polls. Using Monte Carlo simulation, I can generate many such scenarios, and tally the results to predict the range of likely outcomes and the probability of various outcomes.

For this simulation, I used the latest Real Clear Politics poll averages of 14 battleground states - AZ, CO, FL, GA, IN, MO, MT, NV, NH, NM, NC, OH, VA, and WV. Scroll down for details about the model and its assumptions after the results.**RESULTS ***(from 10,000 simulations)**:*

- Most likely number of Obama electoral votes => 364
- Probability of Obama win => 99.99%
- Best case / worst case scenario => 393 / 269 EV
- States with the greatest impact on likely outcomes => FL (57%), NC (18%), MO (10%), IN (9%)

For the inquiring mind, here are the key features / assumptions in my model.

- On a state-by-state basis, undecided voters are allocated 60% to McCain and 40% Obama.
- For each simulation, the likely percentage of Obama votes is calculated by assuming it follows a normal distribution with (a) mean based on the poll results plus undecided allocation and (b) standard deviation based on sample size. I use an avereage sample size based on all the polls used for the RCP average.
- The winner for each state is allocated all of the state's electoral votes (with the exception of Nebraska, where the winner of popular votes gets 3 delegates and the loser gets 2 delegates).
- The results are aggregated for 10,000 simulations to calculate: (a) most likely number of electoral votes for Obama (the "mode"), and (b) probability of Obama winning more than 270 electoral votes.
- States with the greatest impact on likely outcomes are ranked based on their fractional contribution to the variance in Obama EV predictions.