INTERACTIVE ELECTION SIMULATION MODEL  (Excel)
created by TruthIsAll

http://www.geocities.com/electionmodel/InteractiveElectionSimulation.zip

This workbook contains a full analysis of the 2004 election, based on four sets of polls:
(1) Pre-election State polls
(2) Pre-election National Polls (18)
(3) Post-election State exit polls
(4) National Exit poll

The model can be used to run simulations, calculate probabilities and perform "sensitivity analysis" to see the effects of changes in assumptions on the electoral and popular vote.

The model provides a strong circumstantial case for those who believe the election was stolen.

Kerry won the pre-election state and national simulations, which are confirmed by the State and Preliminary National exit polls. Bush won only the Final Exit Poll, which was matched to the recorded vote.

There are only two possible explanations: either the pre-election AND exit polls were wrong - or massive fraud occurred.

The following worksheets are selected by clicking the tab at the bottom of the screen:

Introduction
Model description; links to: polling data sources; EIRS database; related mathematics

Main
Data input and summary analysis
Set calculation code = 1 to run the simulation/projection using final PRE-ELECTION polls.
Set calculation code = 2 to run the simulation based on EXIT polls.

Undecided voter allocation - set to Kerry percentage (default is 75%)
Exit Poll Cluster effect - percentage increase in calculated MoE (default is 30%)

StatePreExit
Monte Carlo Simulation of 200 state pre-election and 200 state exit polls

NatPre
Projections and analysis of 18 national pre-election polls

NatExit
Analysis of National Exit Poll demographic timelines:
a) Preliminary (13047 respondents) updated Nov. 3 at 12:22 am.
b) Final Exit Poll (13660 respondents) updated Nov. 3 at 1:25 pm.

Ask "what-if": analyze the effects of changing demographic weights and percentages on the national totals.

Voted2000
Discussion and Sensitivity Analysis of the "Voted in 2000" demographic.

Vote margin sensitivity to Gore 2000 turnout and Kerry new voter share using actual 2000 weights, assuming 100% Bush 2000 voter turnout.

PrecinctRespOpt
Constrained optimization solution ("Solver" algorithm) for the true vote based on
a) the 2-party vote
b) exit poll precinct error (WPE)
c) response rate for 1250 precincts in 5 partisanship groups.

StateRespOpt
Uses Excel "Solver" to derive a feasible true vote based on
a) the final 2-party vote,
b) State exit poll deviations and
c) response rates for 5 states grouped from high Bush to high Kerry.

Gender
Comparative analysis for state and national exit polls

Census
Demographic Voter statistics from the U.S. Census Bureau, Population Vote Survey, November 2004.

The Gender split matched the state exit poll to within 0.25% and the National exit poll within 0.50%

OHIO
Ohio Exit Poll Demographic Analysis vs. National Exit Poll

STATE POLLS
The model produces the following:
-Popular vote percentage/win probability based on pre-election state polls.
-Electoral win probability based on 200 Monte Carlo simulated election trials
-Exit Poll percentages and deviations from the final recorded vote.

Pre-election state polls are from Zogby, ARG, Gallup, etc. Kerry's projected vote is the poll percentage plus the undecided voter allocation.

Undecided voters traditionally break for the challenger by 60-80%. Adjust this margin up or down to see the effects on popular and electoral votes.

Review the expected electoral vote and win probabilities.

Play "what if" by changing just two inputs: undecided voter allocation and cluster effect.

Calculate the undecided voter allocation necessary for Kerry to win 50% of the popular vote and 270 electoral votes.

Enter the cluster effect as a percentage increase in the theoretical calculated Exit Poll MoE. The rational for the increase is the supposed loss of accuracy due to physical "clustering" of individuals at the poll locations.

The number of states deviating beyond the exit poll MoE will decrease as the cluster effect increases.

Review the following simulation output:
Electoral and popular vote split and win probabilities.
Deviation probabilities for pre-election polls.
Deviation probabilities for exit polls.



NATIONAL POLLS
Kerry had a slight lead in the 18 Pre-election poll weighted average: 47.55% - 47.30% and was poised to win, since historical stats show that challengers win a majority (60%+) of the late undecided vote.

The Preliminary National Exit Poll ( 12:22am, 13047 respondents) followed the 4pm ( 8349 ) and 7:33pm ( 11027 ) timelines. Kerry was leading at each point in the timeline.

The Final National Exit poll (13660 respondents) was posted at 1:25pm.
Demographic weights and percentages were adjusted to match the recorded vote.

Ask "what if" by changing exit poll demographic weights and vote percentages.
You can also change the exit poll "cluster" effect. Note how the popular vote split and corresponding deviation probabilities change.

Exit poll vote percentages do not all sum to 100% horizontally, perhaps due to roundoff. Effects on Kerry/Bush percentages and probabilties are minimal.
Demographics are calculated independently.

Key demographics for what-if analysis:
Gender - Preliminary: Kerry share of female vote: 54% ; Final: 51%.
How Voted in 2000 - Preliminary: 41% Bush / 39% Gore ; Final: 43 / 37%.
Party ID - Preliminary: 38% Democrat / 35% Republican / 27% Independent ; Final: 37 / 37 / 26%


POLL SAMPLE-SIZE AND MARGIN OF ERROR
The Law of Large Numbers is the basis for statistical sampling. All things being equal, polling accuracy is directly related to sample size - the larger the sample, the smaller the margin of error (MoE). In an unbiased random sample, there is a 95% probability that the vote will fall within the MoE of the sample mean.

In the pre-election polls, about 600 were polled in each state (4% MoE). That may seem high, but the simulation effectively consolidates them into a 30,000 national total - and the combination of 50 state polls lowers the national MoE.

In 18 pre-election national polls sample-size ranged from 800 (3.5% MoE) to 3500 (1.7%). The total 27,229 sample reduces the combined MoE to 0.59%.

The post-election state exit polls sampled 73,607 nation-wide, with respondents ranging from 600 (4% MoE) to 2800 (1.8%). The total 73,607 sample-size gives an MoE of just 0.37%.

In the National Exit Poll of 13047 respondents, the MoE, before any "cluster effect", is 0.88%. Kerry won 51%-48%. Assuming a 1,0% MoE, the probability was 97.5% that he would win at least 50% of the vote. The 95% probability that his vote would fall between 50-52% is added to the 2.5% probability that it would exceed 52%.

DEFINITIONS
Monte Carlo Simulation- a randomization process of repeated experimental "trials" applied to a mathematical system model.

This simulation consists of 200 trial "elections" to determine the expected Electoral Vote and win probability.

The state win probability is based on the final exit poll split. A typical state poll consists of 600 sample-size with 4% MoE.

The Electoral Vote is calculated for Kerry and Bush for each of the 200 election trials. The average electoral vote is the arithmetic mean of the 200 trials. The median EV (the middle value) is usually within a few votes of the average.

Margin of error - is based on poll sample size and given by the formula:
MoE = 1.96* Sqrt (P*(1-P)/n) at the 95% confidence level, where P and 1-P is the vote split.


NORMAL DISTRIBUTION
Returns the normal distribution for the specified mean and standard deviation.
This Excel function has a very wide range of applications in statistics, including hypothesis testing.

Syntax
NORMDIST(x,mean,standard_dev,cumulative)
X is the value for which you want the distribution.
Mean is the arithmetic mean of the distribution.
Standard_dev is the standard deviation of the distribution.

Cumulative is a logical value that determines the form of the function.
If cumulative is TRUE, NORMDIST returns the cumulative distribution function; if FALSE, it returns the probability mass function.

EXAMPLE
Calculate the probability Kerry would win Ohio based on the exit poll.

Ohio Exit Poll - 12:22am update, 1963 sample-size
http://www.exitpollz.org/cnn2004epolls/Pres_epolls...

TRY IT YOURSELF: Change the Weights / poll percentages to see the effects on the vote.

Weight Vote Kerry Bush
Male 47% 2.644 51.00% 49.00%
Female 53% 2.981 53.00% 47.00%

Total 100% 52.06% 47.94%
Votes (millions) 5.625 2.928 2.697

Kerry winning margin: 232 thousand votes.


Note: change Sample size and / or Cluster effect to see the effect on the probability:

Sample Size 1963
MoE 2.21%
Cluster effect 20%
Adj. MoE 2.65%
StdDev = 1.35% (Adj. MoE / 1.96)

The input parameters to the Normal Distribution function:
Probability = NORMDIST(Kerry, Bush, StdDev, TRUE)
are given by:
Kerry = 52.06%
Bush = 47.94%
StdDev = 1.35%

Probability Kerry won Ohio for a given cluster effect:
MoE 2.21% 2.43% 2.65% 2.87% 3.10% 3.32%
Cluster 0% 10% 20% 30% 40% 50%

Probability
Kerry won Ohio
96.61% 95.15% 93.59% 91.99% 90.39% 88.82%



BINOMIAL DISTRIBUTION
Returns the individual term binomial distribution probability.
Use BINOMDIST in problems with a fixed number of tests or trials, when the outcomes of any trial are only success or failure,
when trials are independent, and when the probability of success is constant throughout the experiment.
For example, BINOMDIST can calculate the probability that two of the next three babies born are male.

Syntax
BINOMDIST (number_s, trials, probability_s, cumulative)
Number_s is the number of successes in trials.
Trials is the number of independent trials.
Probability_s is the probability of success on each trial.
Cumulative is a logical value that determines the form of the function.

If Cumulative is TRUE, then BINOMDIST returns the cumulative distribution function,
the probability of at most number_s successes.
If Cumulative is FALSE, then BINOMDIST returns the probability mass function,
the probability of exactly number_s successes.

EXAMPLE
Determine the probability that the state exit poll MoE is exceeded in at least N states.

The probability that at least N states would exceed the MoE (non-success) is equal to
1 - the probability that at most N-1 states would fall within the MoE (a success).

P = .025 (1 in 40) is the probability of a given state vote exceeding the MoE.

Therefore the probability that at most N-1 states fall within the MoE is:
Prob = BINOMDIST(N-1, 50, P, TRUE)

N = 16 states exceeded the MoE in favor of Bush.

CALCULATE THE PROBABILITY:
Enter the number of states outside the MoE: 16
Prob (16) = 1- BINOMDIST(15, 50, 0.025, TRUE)

The probability is 5.24E-14 or
1 in 19,083,049,268,519


National Pre-election polls
http://www.pollingreport.com/wh04gen.htm
http://www.economist.com/media/pdf/YouGovS.pdf

Links to all state polls
http://www.exitpollz.org/cnn2004epolls/Pres_epolls

7:33pm Nov 2, 11027 respondents
http://www.exitpollz.org/CNN_national2.htm

12:22am Nov. 3, 13047 respondents
http://www.democraticunderground.com/discuss/duboa...

2:05pm Nov.3, 13660 respondents
http://www.cnn.com/ELECTION/2004/pages/results/sta...




National Exit Poll (pdf)

11/2/04, 3:59pm 8349 respondents: Kerry 51-Bush 48
http://www.exitpollz.org/mitof4zone/US2004G_3737_P...

11/2/04, 7:33pm 11027 respondents: Kerry 51-Bush 48
http://www.exitpollz.org/mitof4zone/US2004G_3798_P...


11/3/04, 1:25pm 13660 respondents: Kerry 48-Bush 51
http://www.exitpollz.org/mitof4zone/US2004G_3970_P...



ELECTION INCIDENT REPORTING SYSTEM (EIRS)
https://voteprotect.org/index.php?display=EIRMapNa...


LINKS TO STATISTICAL AND PROBABILITY TOPICS
http://en.wikipedia.org/wiki/List_of_statistical_t...
http://en.wikipedia.org/wiki/List_of_probability_t...
http://en.wikipedia.org/wiki/Opinion_poll
http://en.wikipedia.org/wiki/Margin_of_error
http://en.wikipedia.org/wiki/Random_sampling
http://en.wikipedia.org/wiki/Standard_deviation
http://en.wikipedia.org/wiki/Standard_score
http://en.wikipedia.org/wiki/Normal_distribution
http://en.wikipedia.org/wiki/Central_limit_theorem
http://en.wikipedia.org/wiki/Correlation
http://en.wikipedia.org/wiki/Illustration_of_the_c...
http://en.wikipedia.org/wiki/Independent_identical...
http://en.wikipedia.org/wiki/Statistical_hypothesi...
http://en.wikipedia.org/wiki/Law_of_large_numbers
http://en.wikipedia.org/wiki/Least_squares
http://en.wikipedia.org/wiki/Odds
http://en.wikipedia.org/wiki/Probability_theory
http://en.wikipedia.org/wiki/Random_data
http://en.wikipedia.org/wiki/Statistical_power
http://en.wikipedia.org/wiki/Testing_hypotheses_su...
http://en.wikipedia.org/wiki/List_of_numerical_ana...