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Category Archives: 2014 Wisconsin and Florida Election

2014 Election Fraud: Four statistical models

2014 Election Fraud:  Four Statistical Models

Richard Charnin
Dec. 28, 2015
Updated: Jan.18, 2016

This post reviews the following statistical models which strongly indicate fraud in the 2014 Governor elections:
1) True Vote Model, 2) Cumulative Vote Shares, 3) Voter Registration vs. Exit Poll Party-ID, 4) Uncounted Votes Cast (Census).

Democratic Vote Shares: Statistical Summary

Dem Vote% CVS TVM Census D/R ExitP D/R Registered
KY 43.8 49.1 48.0 49.3 na 54-39
MD * 47.2 52.9 56.4 59.1 na 55-26
WI 46.7 50.2 51.6 51.3 36-37 43-41
FL 47.1 51.1 49.7 50.9 31-35 39-35
IL 46.4 54.4 54.2 54.8 43-30 47-35
MA 46.6 55.9 55.6 56.5 na 35-11
CO 49.1 na 50.7 53.1 28-32 31-33
GA 44.8 na 48.2 52.2 35-37 39-43
KS 46.1 na 48.3 52.0 25-48 24-44
ME 43.3 na 51.5 52.3 30-31 33-27
MI 46.8 na 52.4 54.3 39-30 44-37
OH 32.9 na 37.7 41.7 32-36 41-42


Cumulative Vote Shares

The CVS method  uses actual precinct votes in each county. The data is sorted by  precinct size. The votes and shares are accumulated and  displayed graphically. Typically, in the biggest counties, Democratic shares peak at the 10% CVS mark and decline at the final 100% (recorded vote). This is counter-intuitive because a) the most populous counties are in urban locations which are strongly Democratic and b) as the number of votes are accumulated, the Law of Large Numbers (LLN) should result in a Steady state of equibrium in which Democratic and Republican vote shares are nearly constant.

Click these links to view the summary 2014 CVS analysis (each has a  link to the precinct votes for each county):  IL  FL  WI  MD MA  KY

The True Vote Model (TVM)

The 2012 presidential election is used as a basis for returning 2014 voters. There are two options for estimating  returning voters: the Recorded Vote and estimated True Vote.

The TVM closely matched the CVS in all governor elections except  for Maryland.  Hogan(R) won the recorded vote by 51.0- 47.2%, a 66,000 vote margin.  Brown(D) won the True Vote by 56.4-41.9%, a 251,000 margin. The CVS analysis understates Brown’s vote since precinct votes were provided only for Election Day; early, provisional and absentee precinct voting were not included. This omission dramatically reduced  Brown’s CVS since he had 54% of the excluded votes.  Click these links to view the 2014 Governor True Vote Model:  MD  IL  FL  WI  KY MA ME  OH KS MI GA CO


Census Population Survey (CPS) Voter Turnout

In each election cycle, the Census Bureau interviews 60,000 households nationwide to estimate  how many were registered and voted in each state.The national margin of error (MoE) is 0.3% for 60,000 respondents at the 90% confidence level. The MoE is approximately 2% for each state.

In 2014, 92.2 million votes were cast  but just 78.8 million recorded. The 13.4 million discrepancy (14.5%) was greater than in any presidential election. What is going on here?

In every one of the 1968-2012 presidential elections,  votes cast exceeded the recorded vote. The percentage of uncounted votes has declined steadily since 1988, from 10.4% to 2.9% in 2012. Uncounted votes peaked at 10.6 million in 1988 and declined to near zero in 2008. Approximately 75% of uncounted votes were Democratic (50% in minority locations).

The recorded vote was adjusted  to total votes cast by adding the uncounted votes. The majority (60-75%) of uncounted votes were  assumed to be Democratic, based on the historical fact that approximately 50% of uncounted votes are in minority locations.

Uncounted Votes = Census Total Votes Cast – Votes Recorded
True Vote (est.) = Recorded Vote + Uncounted vote

Presidential  Votes Cast and Recorded

Cast Recorded Diff Pct
1968 79.0 73.0 6.0 7.6%
1972 85.8 77.7 8.1 9.4%
1976 86.7 81.5 5.2 6.0%
1980 93.1 86.6 6.5 7.0%
1984 101.9 92.7 9.2 9.0%
1988 102.2 91.6 10.6 10.4%
1992 113.9 104.4 9.5 8.3%
1996 105.0 96.4 8.6 8.2%
2000 110.8 105.6 5.2 4.7%
2004 125.7 122.3 3.4 2.7%
2008 131.1 131.4 -0.3 -0.2%
2012 132.9 129.1 3.8 2.9%
2014 92.2 78.8 13.4 14.5%

Political Party Strength 

The simplest measure of  party strength in a state’s voting population is the breakdown-by-party totals from its voter registration statistics from the websites of the Secretaries of State or the Boards of Elections. As of 2014, 28 states and the District of Columbia allow registered voters to indicate a party preference when registering to vote.

In 2014,  the party voter preference/registration split was 40.5D-35.3R-24.2I.  The  2014 National Exit Poll indicated a 35D-36R-28I Party-ID split in forcing a match to the recorded vote (Dem 46.2-Rep 52.9%). Assuming the voter registration split and the Party-ID vote shares, the Democrats  and Republicans were essentially tied.

The registered voter split for the 12 Governor elections in this analysis was 40.6D-34.4R-24.4I, a very close match to the national split.

These 22 states do not allow party preference in voter registration:
Alabama,Arkansas, Georgia, Hawaii, Idaho, Illinois, Indiana, Michigan, Minnesota, Mississippi, Missouri, Montana, North Dakota, Ohio, South Carolina, Tennessee, Texas, Utah, Vermont, Virginia, Washington and Wisconsin.

The partisan “demographics”  were obtained from the state’s party registration statistics (in late 2014 whenever possible). For the 22 states that don’t allow registration by party, Gallup’s annual polling of voter party identification is the next best metric of party strength.

National Exit Poll 2014 Party-ID (match recorded vote)

Party-ID Split Dem Repub Ind
Dem 35% 92% 7% 1%
Rep 36% 5% 94% 1%
Ind 29% 42% 56% 4%
Total 100% 46.2% 52.5% 1.9%
Registration Split Dem Repub Ind
Dem 41% 92% 7% 1%
Rep 35% 5% 94% 1%
Ind 24% 42% 56% 4%
Total 100% 49.6% 48.7% 1.7%

 

Matching the Recorded and True Vote using the Party Registration split

To match the recorded vote,  an implausibly low  percentage of Democrats had to have voted for the Democratic candidate. Note the difference between  the percentage of Democrats required to match the recorded vote and True vote shares. Democratic and Republican candidates usually win approximately 90-92% of  registered Democrats and Republicans, respectively.

Percentage Share of Registered Democrats Required to Match

 Match Recorded Vote True      Vote  Match Recorded  True Vote
MA 58.5 83.9 ME 66.6 92.0
MD 68.9 84.9 OH 53.5 92.1
KY 72.4 81.7 KS 86.1 95.5
WI 88.8 94.7 MI 75.5 88.1
FL 81.3 88.1 GA 87.7 93.3
IL 83.0 91.0 CO 88.6 93.8


 KENTUCKY

Conway (D) lost the recorded vote  by 52.5-43.8% despite the fact that the Democrats led 53.4-38.8% in voter registration. Bevin needed an implausible 24.6% of Democrats to match the recorded vote. Assuming just 81.7% of Democrats voted for Conway, he won by 48.8-47.5%, closely matching the CVS and True Vote.

According to the 2014 Census, 1.525 million total votes were cast in 2014.  In 2015, Conway won by 49.3-47.0% – assuming he had 60% of an estimated 50,000 uncounted votes.

Of 2,298,000 registered  voters, 974,000 (42.4%) voted. If  39% of Democrats voted and Conway had 88%, he won by 49.0-47.3%. If 43% of Democrats voted, he won by 54-42.3%.

Party Reg Split Conway Bevin Curtis
Democrat 53.4% 72.4% 24.6% 3%
Republican 38.8% 4% 92% 4%
Other 7.8% 46% 47% 7%
Recorded 100% 43.8% 52.5% 3.7%
Votes (000) 974 427 511 36

 

Party Reg Split Conway Bevin Curtis
Democrat 53.4% 81.7% 15.3% 3%
Republican 38.8% 4% 92% 4%
Other 7.8% 46% 47% 7%
True Vote 100% 48.8% 47.5% 3.7%
Votes (000) 974 475 463 36

 

Votes Cast Total Conway Bevin Curtis
Recorded 974 426.6 512.0 36.0
Uncounted (est) 50 30.0 18.2 1.9
2014 Census 1024 505 481 38
Adj. Share   49.3% 47.0% 3.7%

 

Party Reg Split Conway Turnout 39%  41% 43%
Democrat 53.4% 88% 18.3% 19.3% 20.2%
Repub 38.8% 6% 0.9% 1.0% 1.0%
Other 7.8% 50% 1.5% 1.6% 1.7%
Conway 49.0% 51.5% 54.0%
Bevin 47.3% 44.8% 42.3%

 

MARYLAND

Hogan (R) won the recorded vote by 51.0-47.3%.  He won the CVS by a whopping Brown(D) had 53.7% of early votes, 45.3% on Election Day and 54.5% of absentee and provisional ballots. Precinct votes on touchscreens and optical scanners were provided for Election Day only.

When 295,000 uncounted votes are added to the recorded vote, Brown is the winner by 51.2-47.0% .  When  Election Day CVS  at the 10% mark is added to the 390,000 early, absentee and provisional votes, Brown is a  52.9-45.5% winner.

 Census Votes (000) Total Brown Hogan Other
True 1,733 977 726 30
Adjusted (Unctd) 295 221 68 5
Total Census 2,028 1,198 794 35
Share   59.1% 39.2% 1.7%

 

Voter Reg Pct Brown Hogan Other
Democrat 54.9% 84.9% 13.1% 2.0%
Republican 25.7% 4% 95% 1.0%
Other 19.4% 45% 53% 2.0%
Share 100% 56.4% 41.9% 1.7%
Total 1,733 977 726 30
Adjusted Total Brown Share Hogan Share Other Share
Early 306 164 53.7% 137 44.8% 4.5 1.5%
Election Day 1,342 608 45.3% 711 52.9% 23.5 1.7%
Absentee/prov 85 46 54.5% 37 43.4% 1.8 2.1%
 Recorded 1,733 819 47.25% 884 51.0% 30 1.7%
 CVS adj
Early/abs/prov 390 210 53.9% 174 44.5% 6 1.6%
CVS @ 10% 1,391 693 52.5% 603 45.7% 23 1.7%
Adj. Total 1,709 904 52.9% 777 45.4% 29 1.7%

Notes:- Beth Clarkson, a PhD in statistics, did an analysis of 2014 cumulative vote share anomalies: How Trustworthy are Electronic Voting Systems in the US

– A statistical study by G.F.
Webb of Vanderbilt University reveals a correlation of large precincts and increased fraction of Republican votes:Precinct
 Size
 Matters: ­
The 
Large
 Precinct
 Bias
 in
 US 
Presidential
 Elections

– Francois Choquette and James Johnson exposed anomalies in the 2012 primaries:2008/2012 Election Anomalies, Results, Analysis and Concerns

– Kathy Dopp is a mathematician and an expert on election auditing. She has written a comprehensive analysis of the 2014 elections:
Were the 2014 United States Senatorial and Gubernatorial Elections Manipulated?  Dopp wrote:
Is it possible electronic vote-count manipulation determines who controls government in the United States? The probability that the disparities between predicted and reported 2014 election vote margins were caused by random sampling error is virtually zero. A method for extending and simplifying fuzzy set qualitative comparative analysis (FsQCA)’s measure for necessity reveals that lack of effective post-election audits is a necessary condition for the occurrence of high levels of disparity between statewide polls and election results. Maryland’s 2014 gubernatorial contest is consistent with an explanation of vote miscount having altered its outcome.  An analysis of Maryland’s partisan voter registration, turnout, and vote data by ballot type statistically confirms vote miscount as an explanation for its unexpected outcome.

Maryland, Illinois, Florida, and Kansas gubernatorial contests exhibited sufficient disparities between polls and election results (PED) to alter election outcomes; all used inauditable voting systems or failed to conduct post-election audits (PEA)s. Vermont’s PED was within one percent of sufficient to alter its outcome. In Nevada, Tennessee, New York, Ohio, and South Dakota PED were large but smaller than winning margins.

Kansas and North Carolina senatorial contests exhibited sufficient PED to alter election outcomes and no audits were conducted. Virginia’s PED was within one percent of sufficient to alter its outcome. In Arkansas, Wyoming, Tennessee, Kentucky, and Nebraska PED magnitude were large but smaller than winning margins.

A case study of Maryland’s unexpected 2014 gubernatorial outcome affirms there is, as yet, only an explanation of vote manipulation consistent with the statistical disparity patterns in Maryland’s pre-election poll predictions, and its partisan voter registration, turnout and vote data by ballot type.

…………………………………………………………………………..

http://www.census.gov/hhes/www/socdemo/voting/publications/other/State%20User%20Note_Final.pdf

Look inside the books:
Reclaiming Science: The JFK Conspiracy
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Exit Poll

A Collage of Election Fraud Graphics

LINKS TO WEB/BLOG POSTS FROM 2004

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Florida 2014 Governor Election Fraud: Cumulative Precinct Vote Shares

Florida 2014 Governor Election Fraud: Cumulative Precinct Vote Shares

Richard Charnin
Feb.11, 2015
Updated: Aug.8, 2015
https://richardcharnin.wordpress.com/my-book/

Scott(R) defeated Crist(D) by 64,145 votes out of 5.95 million cast (48.1-47.1%). Third-party candidates had 4.8%.

2014 was a replay of the 2010 election in which Scott defeated Sink(D) by 62,000 votes (49.6- 48.4%). Sink won the unadjusted exit poll (3,150 respondents): 50.8-45.4-3.8%. The margin of error was 2%.

Previous posts applied cumulative vote share analysis using graphics to confirm 2014 election fraud in Wisconsin and South Dakota. This post will do the same for the Florida governor election.

Cumulative Vote shares
Precinct votes for 12 of 67 Florida counties were downloaded. The 12 counties comprised 58.25% of the total state vote. The analysis indicates that approximately 150,000 Crist votes flipped to Scott in the 12 counties: Brevard Broward Dade Duval Hillsborough Lee Marion Orange Palm Beach Pinellas Polk Volusia

The 12 counties comprised 58.25% of the total state vote. The analysis indicates that approximately 150,000 Crist votes flipped to Scott in the 12 counties.

Crist had 47.07% of 5.95 million total votes. He had 54.39% of 3.47 million votes in the 12 counties and 36.84% of 2.48 million votes in the other 55 counties.

The data was sorted in ascending order from the smallest to the largest precincts. In each of the 12 counties, the trend never reversed: Crist‘s vote share declined in every case.

There was a 4.13% decline in Crist’s vote share from the 25% mark to the final (100%). His shares declined from 25-50%, 50-75% to 75-100% of the vote. The probability of ALL changes in shares of moving in one direction (to Scott) is the same as flipping a coin 36 times and getting all heads! P= 0.5^36 = 1.46E-11 or 1 in 68.7 billion!

https://docs.google.com/spreadsheets/d/17naKWzaLDkRaYfgiTAJfkJ5pFDoI_rv4HXfXcLyD4Ls/edit#gid=1299990885

A Sensitivity Analysis of displays a range of actual Crist vote shares in 12 counties over the 25,50,75% and final 100% recorded vote. These are combined with his assumed vote shares ranging from 37-47% for the other 55 counties. Crist won 42 of the 44 scenarios.

Assuming Crist had a 44% share in the 55 small counties
-At the 25% mark Crist is a 52.6-42.8% winner given his 58.5% share in the 12 big counties.
-At the 50% mark Crist is a 51.5-43.6% winner given his 56.9% share in the 12 big counties.
-At the 75% mark Crist is a 50.9-44.3% winner given his 55.8% share in the 12 big counties.
-At the 100% mark Crist is a 50.1-45.2% winner given his 54.4% share in the 12 big counties.

Since the CVS analysis is based on recorded votes, not the true vote, they appear to discount Crist’s true shares in the 12 biggest counties at the 25,50,75 and final 100% mark.

IMPLAUSIBLE EXIT POLL
The FL exit poll indicated that 35% of voters were Republicans and just 31% Democratic. This ratio is highly suspect. Note that the Party-ID percentages only sum to 99%. This is significant in an election in which Scott won by 1%.

There are 500,000 more registered Democrats than Republicans

Total.........Democrats...Republicans..Other
11,931,533...4,628,178 4,172,232 3,131,123
..............38.79%....34.97%....26.24%

The adjusted exit poll gives the GOP a 35-31% Party-ID edge.
Party-ID was adjusted to match the recorded vote.
Crist had 91% of Democrats while Scott had just 88% of Republicans.
Note: The Party-ID total is 99%; Other (third party) shares total 98%)

................Pct.Crist.Scott.Other
Democrat........31.0% 91.0% 6.00% 3.0%
Republican......35.0% 10.0% 88.0% 2.0%
Other...........33.0% 46.0% 44.0 8.0%
Total...........99.0% 46.9% 47.2% 4.3%
Votes..........5.877 2.783 2.800 0.253

Change the Party-ID percentage to the actual registration mix.
Crist is the winner by 368,000 votes.
................Pct..Crist.Scott.Other
Democrat........38.8% 91.0% 6.00% 3.0%
Republican......35.0% 10.0% 88.0% 2.0%
Other...........26.2% 46.0% 44.0% 8.0%
Total...........100.% 50.9% 44.7% 4.0%
Votes...........5.936 3.019 2.651 0.235

Sensitivity Analysis

.........Crist share of 55 counties
....Share .. 47%...46%...45%...44%
...........Total Crist Share
25% 58.52%.. 53.71 53.29 52.88 52.46
50% 56.94%.. 52.79 52.37 51.95 51.54
75% 55.83%.. 52.15 51.73 51.31 50.89
100% 54.39%. 51.31 50.89 50.47 50.05
................ Crist Margin
25% 21.83%.. 12.21% 11.38% 10.54% 9.71%
50% 18.67%.. 10.37% 9.53% 8.70% 7.86%
75% 16.45%.. 9.08% 8.25% 7.41% 6.58%
100% 13.57%. 7.40% 6.57% 5.73% 4.90%

........ Crist cumulative precinct vote shares
County..........Votes... 25% 50% 75% 100% %Chg Vote Chg

Brevard.........207,638 45.6 44.2 44.5 43.8 -1.8 -3,737
Broward.........457,344 71.8 71.0 71.0 69.7 -2.1 -9,604
Dade............509,738 60.9 60.7 60.4 59.8 -1.1 -5,607
Duval...........257,773 56.0 46.5 45.1 43.3 -12.7 -32,737
Hillsborough....350,022 57.4 55.7 54.1 51.5 -5.9 -20,651

Lee.............201,416 45.2 43.1 41.6 39.4 -5.8 -11,682
Marion..........112,571 45.9 44.2 41.9 41.2 -4.7 -5,291
Orange..........292,584 64.6 60.1 58.6 56.2 -8.4 -24,577
Palm Beach......407,070 61.7 62.4 61.9 60.6 -1.1 -4,478
Pinellas........328,201 61.2 58.9 56.7 56.0 -5.2 -17,066

Polk............177,609 48.6 47.4 46.4 44.7 -3.9 -6,927
Volusia.........165,064 51.2 51.8 49.4 48.1 -3.1 -5,117

Total.........3,467,030 58.7 56.8 55.8 54.4 -4.3 -147,475


This result confirms results from Governor True Vote analysis for the 2010 and 2014 elections.

The Law of Large Numbers
Why does a baseball players batting average fluctuate less and less as the number of at bats increase? How come in coin flipping the percentage of heads approaches 50.0% as the number of flips increase? One would expect Crist’s cumulative vote share to INCREASE SLIGHTLY as PRECINCT SIZE INCREASES since the larger urban districts are usually more Democratic than the smaller rural districts. But Crist’s share decreased in all 12 counties – a counter-intuitive result.

Actual precinct voting data shows that the changes in vote shares moving in the direction of Scott are impossible statistically and demographically – indicating fraud. Cumulative vote share analysis (CVS) is a tool for uncovering the most fraudulent counties – such as Duval. The overall county results confirmed the True Vote Model (TVM) and the 2010 unadjusted exit poll.

Dade, Palm Beach and Broward are large, highly Democratic counties. The percentage vote switches from Crist to Scott from the 25,000 vote mark to the final 100% were -1.1%, -3.1%, -2.1%, respectively. Therefore the lines are nearly flat.

2014 was an exact match to 2010
In previous posts, we concluded that Scott stole the 2010 and 2014 elections. In 2010, Scott won the recorded vote by 49.6-48.4% (62,000 votes) or 50.59% of the 2-party vote. Sink, the Democrat, won the unadjusted exit poll by 50.8-45.4% (283,000 votes).

In 2014, Scott won the recorded vote by 48.2-47.1%. His 2-party vote share (50.58%) was within 0.01% of his 2010 (50.59%) share! Crist won the True Vote by 52.0-48.0%. https://docs.google.com/spreadsheets/d/1SnErWihwCvq5puGw3sBF9E4jr585XV2NChqvxGObLAU/edit#gid=841488888

Florida 2014 Exit Poll
The poll was forced to match forced to match the bogus recorded vote by adjusting the unavailable actual exit poll results. Exit pollsters ALWAYS assume ZERO election fraud. It is standard operating procedure and has no scientific basis. They are complicit in perpetuating the fraud. The exit pollsters had to force a match to the bogus FL recorded vote in every demographic crosstab. https://docs.google.com/spreadsheets/d/1SnErWihwCvq5puGw3sBF9E4jr585XV2NChqvxGObLAU/edit#gid=678958238

For example, the Party_ID crosstab had to be adjusted to an implausible Dem 31-Rep 35-Ind 33%. A plausible (conservative) 34-33-33% split results in Crist winning by 49.4-45.6%. Note that 91% of Democrats voted for Crist and 88% of Republicans voted for Scott. Crist won Independents by 46-44%. https://richardcharnin.wordpress.com/2014/11/14/florida-2014-governor-true-voteexit-poll-analysis-indicates-fraud/

View the cumulative precinct votes, shares and corresponding graph for the following counties.
https://docs.google.com/spreadsheets/d/17naKWzaLDkRaYfgiTAJfkJ5pFDoI_rv4HXfXcLyD4Ls/edit#gid=0

Lee

Palm Beach

Brevard

Orange

Pinellas

Polk

Volusia

Marion

Hillsborough

Dade

Duval

Broward

 

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2014 WI and FL Governor election fraud: Adjusting the exit poll Party-ID mix

2014 WI and FL Governor: Exit Poll Party-ID crosstabs adjusted to match the recorded vote

Richard Charnin
Dec. 9, 2014

Look inside the books:
Reclaiming Science:The JFK Conspiracy
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts

JFK Blog Posts
Probability/ Statistical Analysis Spreadsheets:
JFK Calc: Suspicious Deaths, Source of Shots Surveys;
Election Fraud: True Vote Models, State and National Unadjusted Exit Polls

In prior posts, we analyzed how the 2014 Governor exit polls in Wisconsin and Florida were adjusted to match the recorded vote (by changing how returning voters said they voted in the prior election). In this post, we will focus on voter Party-ID and show how it was adjusted.

Florida maintains voter party registration statistics. There are no such stats in Wisconsin, but we have pre-election polls from 2004-2012 which provide a good estimate of the mix.

In order to match the recorded votes in WI and FL, all exit poll demographic crosstabs must be adjusted. The Party-ID crosstab is an important example since it can be compared to other polls which asked for party affiliation.

We will compare bogus Party-ID percentages in the adjusted exit poll (in order to force a match to the bogus recorded shares) to actual (FL) or poll (WI) Party-ID percentages in order to approximate the True Vote. We use the adjusted exit poll vote shares assuming they are essentially accurate. Therefore, adjustments to the Party-ID mix must be made to force the exit poll to match the recorded vote.

Florida

The pollsters increased registered third-party voters by nearly 8%, reduced Democrats by 8% with no change in the 35% Republican Party_ID. This had the effect of reducing Crists’ share by 4% while increasing Scott’s by 2.5%.

Florida 2014 Exit Poll (adjusted to match the recorded vote)
PARTY-ID........Mix Crist Scott Other
Democrat........31% 91% 6% 3%
Republican......35% 10% 88% 2%
Other...........33% 46% 44% 8%

Total...........99% 46.9% 47.2% 4.9%

PARTY-ID (based on actual 2014 Registration totals)
PARTY-ID........Mix Crist Scott Other
Democrat........38.8% 91% 6% 3%
Republican......35.0% 10% 88% 2%
Other...........26.2% 46% 44% 10% (changed to 10% to equal 100%)

Total..........100.0% 50.9% 44.7% 4.4%

http://election.dos.state.fl.us/voter-registration/statistics/pdf/2014/GEN2014_CountyParty.pdf

Wisconsin

Democratic Party-ID was 30.6% in 2004 and increased in three of the next four years to 35.6% in 2008. Republican Party-ID decreased from 31.3% in 2004 to 28.6% in 2008.

In the 2014 WI Governor exit poll, the Democratic Party-ID share was 5% higher than the Marist poll, but the Republican ID share increased by 11%. The gains were at the expense of total third-parties: Party-ID declined by a whopping 16%.

Party-ID
............. Dem Rep Other

2004...... 30.6% 31.3% 29.1%
2008...... 35.6% 28.6% 35.8%
2012...... 31.0% 26.0% 43.0% (Marist Poll)

WISCONSIN 2014 Exit Poll
(Party-ID mix adjusted to match the recorded vote)

Party-ID........Pct Burke Walker Other
Democrat........36.0% 93.0% 6.00% 1.0%
Republican......37.0% 4.00% 96.0% 0.0%
Other...........27.0% 43.0% 54.0% 3.0%

Total..........100.% 46.6% 52.3% 1.1%
Votes..........5.877 2.755 2.772 0.250
Margin......................... 0.174

TRUE VOTE
(Party-ID mix based on 2012 Marist poll)

PARTY-ID........Pct Burke Walker Other
Democrat........31.0% 93.0% 6.00% 1.0%
Republican......26.0% 4.00% 96.0% 0.0%
Other...........43.0% 49.0% 49.0% 2.0%

Total..........100% 50.9% 47.9% 1.20%
Votes..........5.94 2.92 2.736 0.246
Margin................. 0.181

--------------------------------------------------------------------------
ILLINOIS 2014 Exit Poll
(Party-ID mix adjusted to match the recorded vote)

PARTY-ID Pct Quinn Rauner Other
Democrat........43.0% 85.0% 13.0% 2.0%
Republican......30.0% 5.00% 93.0% 2.0%
Other...........26.0% 29.0% 64.0% 7.0%

Total...........99.0% 45.6% 50.1% 3.3%
Votes...........3.626 1.653 1.817 0.118
Margin..........................0.164

TRUE VOTE
PARTY ID........Pct Quinn Rauner Other
Democrat........43.0% 87.0% 11.0% 2.0%
Republican......30.0 5.00% 93.0% 2.0%
Other...........27.0% 44.0% 48.0% 8.0%

Total...........100% 50.4% 45.1% 3.5%
Votes...........3.626 1.825 1.635 0.128
Margin..................0.190

An excellent paper from mathematician Kathy Dopp:
http://electionmathematics.org/em-audits/US/2014/USElections2014.pdf

http://blog.lib.umn.edu/cspg/smartpolitics/2009/02/democrats_lure_independents_to_1.php
http://politicalarithmetik.blogspot.com/2008/06/trends-in-party-identification-in.html

 

Wisconsin 2014 Governor: Cumulative Ward Voting Indicates Fraud

Wisconsin 2014 Governor: Cumulative Ward Voting Indicates Fraud

Richard Charnin
Dec.2, 2014
Updated: Dec.2, 2015

Look inside the books:
Reclaiming Science:The JFK Conspiracy
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts

Index of Wisconsin Blog Posts

JFK Blog Posts
Probability/ Statistical Analysis Spreadsheets:
JFK Calc: Suspicious Deaths, Source of Shots Surveys;
Election Fraud: True Vote Models, State and National Unadjusted Exit Polls

A total of 2,382,055 votes were recorded:
Burke: 1,112,260 (46.69%)
Walker:1,242,413 (52.16%)
Other: 27,383 (1.15%)

The 2014 Wisconsin Governor Cumulative County vote share analysis for all units/wards is available in a spreadsheet for viewing. Vote shares are sorted by increasing ward size for each county. The graphs look strikingly similar to the equivalents in the 2012 recall (especially Milwaukee and Racine). This indicates that the 2012 vote theft strategy was repeated in 2014. If it worked in the recall, why change it? Cumulative vote graphs for the largest counties are located adjacent to the unit/ward vote counts.
https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdEhqXzdlbUhZT1Vic3RSQmU2cUVkc3c&usp=sharing#gid=9

In Milwaukee County, Walker vote shares increased as a function of Unit/Ward size. The increase can be considered as evidence of fraud. One would expect that the lines would be nearly parallel after 90,000 votes. But even parallel lines could indicate constant fraud throughout the county. See the graph below.

Examination
 of 
precinct 
level 
data
 in 
US
 presidential 
elections 
reveals
 a 
correlation
 of
 large
 precincts 
and 
increased
 fraction
 of
 Republican
 votes.
http://arxiv.org/pdf/1410.8868.pdf

The counties that look the most suspicious by the upward slope of Walker shares in large units and wards are Ashland, Brown, Kenosha, Dane, Eau Claire, Jefferson, Milwaukee, Racine, Sheboygan, Winnebago, Waukesha. Of course, a flat line could indicate that fraud is uniform throughout the county.

The spreadsheet can be used as a reference. It will be be enhanced in the near future. Let me know what features you would like to see. View the voting data and graphics in the sheets: Adams-Menominee and Milwaukee-Wood.

Wisconsin 2014 Governor: Total State Cumulative Vote shares
Note how Walker’s vote share initially declines in the smallest wards and reverses trend as the size of wards increase (at the 1 million mark). This is counter-intuitive: Walker’s share should continue the downward trend since larger wards are generally in Democratic strongholds (Dane, Milwaukee..).

Cumulative Vote Shares
https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdEhqXzdlbUhZT1Vic3RSQmU2cUVkc3c&usp=sheets_web#gid=12

County size
Burke had 55.9% in the TOP 15 counties at the 10% CVS mark. Added to the final recorded shares of the other 57 counties, Burke won the election by 52.0-46.9%.

Burke’s total vote dropped by 61,000  from the 25% mark.
Her share fell by 4.8% in the largest 15 counties , increased by 2.4% in the middle 15 and by 0.8% in the 15 smallest . This is a strong indicator of fraud in the biggest counties.

Democratic strongholds
Burke’s share fell by 6.5% in counties in which she was leading at the 25% cumulative vote mark. This is an indicator of fraud in Democratic strongholds.

Correlation
There was a -0.39 statistical correlation between the change in Burke’s total county shares and county vote size and a  corresponding -0.35 correlation in the Democratic-leaning counties (at least 50% at the 25% mark). The correlation is near zero in the middle 15 and smallest 15 counties. This is another indicator of fraud in the largest counties (primarily Milwaukee).

Democratic Vote Share Trend: 5 elections,  15 counties
Obama had 63% in the unadjusted 2008 WI exit poll and 56% recorded, closely matching his CVS share for 15 counties. The unadjusted exit polls are not available for 2010-2014.


Election........Votes. 25%...50%..100% Change
2008 Obama......1853.. 62.4 60.6 57.1... 5.3
2010 Feingold...1375.. 54.7 52.4 48.7... 6.0
2010 Barrett....1372.. 55.0 51.9 48.2... 6.8
2012 Barrett....1551.. 54.2 52.1 48.1... 6.1
2014 Burke......1511.. 54.0 52.2 48.5... 5.5

Burke.......Vote...25%..50%..75%..100%.....Correl Chg
Total.......2385..49.2 48.6 47.5 46.7.... -0.39 -2.6

Top 15......1573.. 53.5 52.0 50.2 48.6... -0.23 -4.9
Mid 15.......242.. 41.0 41.2 41.6 43.1.... 0.01 2.1
Low 15........73.. 43.5 42.6 42.7 43.7.... 0.11 0.2

Burke >50... 935.. 67.3 65.2 62.7 60.8.... -0.35 -6.5

County....... Vote..25 50 75 100% .................. %chg Votechg
Adams............ 8.. 46 46 47 46....................... 0 0.00
Ashland.......... 7.. 59 61 64 63....................... 4 0.26
Barron.......... 17.. 39 39 40 41....................... 2 0.34
Bayfield......... 8.. 54 57 57 61....................... 7 0.56
Brown.......... 100.. 46 44 42 41...................... -5 -5.01

Buffalo.......... 6.. 40 38 40 41....................... 1 0.06
Burnett.......... 7.. 39 41 41 40....................... 1 0.07
Calumet......... 21.. 29 34 34 34....................... 5 1.07
Chippewa........ 25.. 37 42 42 42....................... 5 1.23
Clark........... 11.. 36 34 34 34...................... -2 -0.23

Columbia........ 25.. 43 48 50 51....................... 8 1.98
Crawford......... 6.. 55 55 43 51...................... -4 -0.25
Dane........... 240.. 70 71 71 70....................... 0 0.00
Dodge........... 57.. 29 32 34 36....................... 7 3.98
Door............ 15.. 43 44 45 45....................... 2 0.30

Douglas......... 16.. 54 58 61 61....................... 7 1.10
Dunn............ 15.. 41 43 43 46....................... 5 0.76
EauClaire....... 42.. 49 52 52 50....................... 1 0.42
Florence......... 2.. 28 30 30 31....................... 3 0.06
FonduLac........ 43.. 34 37 36 35....................... 1 0.43

Forest........... 4.. 51 47 44 44...................... -7 -0.25
Grant........... 19.. 44 45 46 48....................... 4 0.77
Green........... 15.. 49 48 51 52....................... 3 0.46
GreenLake........ 7.. 30 28 30 31....................... 1  0.07
Iowa............ 11.. 55 54 55 56....................... 1  0.11

Iron............. 3.. 40 37 38 38...................... -2 -0.06
Jackson.......... 8.. 48 47 47 48....................... 0 0.00
Jefferson....... 36.. 43 39 38 39 ..................... -4 -1.43
Juneau........... 9.. 44 43 45 45....................... 1 0.09
Kenosha......... 56.. 60 57 52 48..................... -12 -6.78

Kewaunee......... 9.. 38 35 33 37...................... -1 -0.09
La Crosse....... 48.. 57 55 54 53 ..................... -4 -1.94
Lafayette........ 6.. 44 44 46 48....................... 4 0.25
Langlade......... 8.. 34 36 36 34....................... 0 0.00
Lincoln......... 12.. 42 43 43 42....................... 0 0.00

Manitowoc....... 34.. 30 34 37 37....................... 7 2.38
Marathon........ 57.. 34 37 38 38....................... 4 2.26
Marinette....... 15.. 35 34 36 38....................... 3 0.46
Marquette........ 6.. 44 41 42 42...................... -2 -0.13
Menominee........ 1.. 75 75 75 75....................... 0 0.00

Milwaukee...... 368.. 74 70 66 63 .................... -11 -40.48
Monroe.......... 15.. 38 38 31 42....................... 4 0.60
Oconto.......... 16.. 34 34 34 35....................... 1 0.16
Oneida.......... 17.. 48 43 43 42...................... -6 -1.02
Outagamie....... 74.. 42 42 41 39...................... -3 -2.22

Ozaukee......... 47.. 30 31 29 29...................... -1 -0.47
Pepin............ 3.. 40 39 42 42....................... 2 0.06
Pierce...........15.. 41 43 43 46....................... 5 0.75
Polk.............16.. 41 41 41 41....................... 0 0.00
Portage......... 30.. 45 50 51 50....................... 5 1.50

Price............ 7.. 39 38 40 42....................... 3 0.21
Racine.......... 80.. 62 55 48 45..................... -17 -13.60
Richland......... 7.. 55 51 49 48...................... -7 -0.49
Rock............ 58.. 55 55 56 56....................... 1 0.58
Rusk............. 6.. 40 36 37 39...................... -1 -0.06

Sauk............ 26.. 55 55 56 56....................... 1 0.26
Sawyer........... 7.. 41 41 43 44....................... 3 0.21
Shawano......... 17.. 37 34 35 34...................... -3 -0.51
Sheboygan....... 50.. 42 39 38 36...................... -6 -3.00
St. Croix....... 34.. 39 41 41 39....................... 0 0.00

Taylor........... 8.. 32 28 27 29...................... -3 -0.24
Trempeleau...... 11.. 48 49 48 46...................... -2 -0.22
Vernon.......... 12.. 47 48 48 50....................... 3 0.36
Vilas........... 11.. 34 35 38 37....................... 3 0.33
Walworth........ 40.. 36 36 34 35...................... -1 -0.40

Washburn......... 7.. 42 41 42 43....................... 1 0.07
Washington...... 66.. 26 25 24 23...................... -3 -1.98
Waukesha....... 203.. 30 29 28 27...................... -3 -6.09
Waupaca......... 21.. 32 34 34 36....................... 4 0.84
Waushara........ 10.. 38 35 37 37...................... -1 -0.10

Winnebago....... 69.. 46 46 46 44...................... -2 -1.38
Wood............ 31.. 36 38 40 41....................... 5 1.55

Compare the 2012 recall cumulative county vote trend analysis to 2014. https://richardcharnin.wordpress.com/2012/12/09/walker-recall-county-cumulative-vote-trend-by-ward-group/

https://docs.google.com/spreadsheets/d/1Fkvjx_XW-VuJ89WlTONZoSLiqj-T-8RakeV0_N9iqyQ/pubchart?oid=2140563995&format=interactive

 

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Wisconsin 2014 Governor True Vote/Exit Poll Analysis Indicates Fraud

Wisconsin 2014 Governor True Vote/Exit Poll Analysis Indicates Fraud

Richard Charnin
Nov.19, 2014
Update: Aug. 16, 2016

Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Election Fraud: True Vote Models, State and National Unadjusted Exit Polls
LINKS TO WEB/BLOG POSTS FROM 2004

After 12 years of posting election fraud statistical models, I decided not to forecast the 2014 election or do a post-election True Vote analysis. Systemic Election Fraud was  proven beyond any doubt, so why bother? Nothing has changed, the media remains mute on the fraud and congress refuses to do anything about it.

I  had worked closely with Wisconsin election reform activists on the 2011 Supreme Court election, the state recalls and Walker recall.   When I was asked to look into the 2014 WI governor election, I felt like Al Pacino in Godfather III: Just when I thought I was out of it, they pulled me back in again. Since I decided to bypass 2014, I did not even know who was running against Walker.

The key to understanding how elections are rigged is to study the exit polls and cumulative vote shares.The pattern keeps repeating: exit polls are adjusted to match the recorded vote. It’s a fact. The pollsters admit it, but claim it is to correct the errant polls.  The assumption is that the recorded vote count is pristine and there is no fraud. At least that is what the pollsters and pundits would like us to believe.

Unadjusted exit polls are not released until years later, so we are left with the adjusted polls (national, state, governor) for clues. In order to adjust the exit poll to match the recorded vote, the returning voter mix from the previous election and/or each candidate’s share of returning and new voters must be changed. All crosstabs must be adjusted. I have stated this often in posts as far back as 2004 as well as in my books. In turned out that the 2014 WI election was 2012 deja vu all over again.

To analyze the 2014 Wisconsin Governor race, I created 2014WIGov.  It contains the following worksheets (sheet names in quotes):
– 2014 National House Exit Poll (‘2014 NEP’)
– 2014 Wisconsin Gov. Exit Poll (‘WI Exit Poll’)
– 2014 Wisconsin County Vote vs. 2012 Recall Vote (“Counties’)
– 2014 Wisconsin Governor True Vote Model (‘True Vote’)

View the: 2014 Wisconsin Governor True Vote Model

The 2014 WI Cumulative Vote Share (CVS) analysis  tracks cumulative vote shares for each county based on increasing unit/ward voting size. The odd pattern of increasing Walker vote shares in large Democratic counties is similar to the 2012 WI recall. This counter-intuitive trend is highly indicative of fraud. View the  2014 Wisconsin Governor Cumulative County/Ward Vote shares and graphs

2014 National Exit Poll (forced to match the recorded vote)
This sheet contains a selected set of cross tabs (demographics). The Gender demographic is within 0.1% of the recorded vote. The theoretical margin of error was approximately 2%. The probability of the 0.1% adjusted exit poll deviation from the recorded vote is close to zero – only because the pollsters forced the match. But that’s not news. It’s standard operating procedure -and obviously unscientific. It’s like a serial thief daring the police to stop him, but they don’t even though they have his fingerprints.

WI Exit Poll (forced to match the recorded vote)
Like virtually all exit polls, it was forced to match the bogus recorded vote by adjusting the number of returning voters to favor the GOP. Returning Walker voters comprised 50% of the 2014 vote total while Barrett voters at 35%. The 15% differential is much higher than Walker’s 7% recorded margin in 2012. But consider that Barrett likely won the 2012 True Vote by 6% – and a whopping 21% discrepancy in margin. Just as in every presidential exit poll, the returning voter percentages were implausible. How could there be a 15% excess of returning Walker 2012 voters over returning Barrett voters?

In the “How Voted in 2012” cross tab, vote shares are missing for Other (3%) and New Voters (DNV 11%). The result is a Walker landslide by 55.4-43.1%, a whopping 12.3% margin. But he had a bogus 52.9% recorded share. The two basic clues that the 2014 election was fixed are obvious from the adjusted exit poll:
1) The 2012 returning voter mix is highly implausible.
2) Vote shares for 14% of the 2014 electorate are not available.

The standard election fraud “tell” is that the returning voter mix has been adjusted to increase the Republican share. When the mix is changed to a feasible Barrett/Walker 45/41% mix, Burke is the winner by 52.3-47.3%

WISCONSIN 2014 EXIT POLL (forced to match recorded vote)
GENDER..........Pct Burke Walker
Male............49% 39.0% 60.0%
Female..........51% 54.0% 45.0%
Total..........100% 46.7% 52.4%
Recorded........... 47.1% 52.9%
Difference........ -0.46% -0.54%
VOTED IN 2012 RECALL (suspicious turnout in 2014 and 14% na)
2012……………….. Pct Burke Walker
Tom Barrett……..35% 96.0% 04.0%
Scott Walker…….50% 05.0% 94.0%
Other ………………3% 50.0% 50.0% (na, set to 50/50)
DNV ……………….11% 50.0% 50.0% (na, set to 50/50)
Recorded…………99% 43.1% 55.4%
TRUE VOTE
……………………..Pct Burke Walker
Tom Barrett…… 45% 96.0% 4.0% (set to plausible 45/41% returning voter mix)
Scott Walker……41% 05.0% 94.0%
Other……………..3% 50.0% 50.0%
DNV………………11% 52.0% 48.0% (adjust new voter shares)
TOTAL………….100% 52.5% 47.1%

TRUE VOTE MODEL

The model is based on 2012 returning voters and 2014 vote share percentages. In the Base Case scenario, Burke had 52.2%  and won by 107,000 votes.

1) Barrett had a 53% True Vote in the 2012 recall
2) 93% turnout of 2012 living voters in 2014
3) Burke had 92% of returning Barrett voters
4) Burke had 7% of returning Walker voters
5) Burke had 54% of new voters.

The Sensitivity analysis shows Burke’s total vote shares and margins for alternative scenarios of vote share and turnout of 2012 voters.

CUMULATIVE VOTE SHARES

Counties
In 2014, there was a significant 0.24 correlation between Walker’s  county votes and turnout (it was 0.28 in the 2012 recall). This measure indicates that as turnout increased, so did Walker’s vote share. But this is counter-intuitive; strong turnout always favors the Democrats. Burke’s total vote dropped by 61,500 (2.57%) from the 25% mark.

County size
Burke’s share fell by 4.8% in the largest 15 counties, but increased by 2.3% in the middle 15 and 0.67% in the 15 smallest. This is a strong indicator of fraud in the biggest counties.

Democratic strongholds
Burke’s share fell by 6.5% in counties in which she was leading the 25% vote mark. This is an indicator of fraud in Democratic strongholds.

Correlation
There was a -0.37 statistical correlation between the change in Burke’s county shares and county vote size. This is another indicator of fraud in the biggest counties (primarily Milwaukee).

Democratic Vote Share Trend - 15 counties
Election.....Votes..25%...50%..100% Change
Average.......1532 56.1% 53.8% 50.1% 5.9%
2008 Obama……..1853 62.4% 60.7% 57.1% 5.3%
2010 Feingold……1375 54.7% 52.5% 48.7% 6.0%
2010 Barrett……..1372 55.0% 51.9% 48.2% 6.8%
2012 Barrett……..1551 54.2% 52.1% 48.1% 6.1%
2014 Burke……….1511 53.0% 52.2% 48.5% 5.5%
Vote change…..Vote….25%…50%..75%..100%
Votes…………..-61.49 1,174 1,158 1,133 1,113
% Change…………….-2.57 -0.67 -1.07 -0.84
…………..Vote..25%..50%..75%..100%….Correl..% Change
Total……2,385 49.2 48.5 47.5 46.6.. -0.37… -2.6
Top 15…1,573 53.4 52.0 50.2 48.6.. -0.23… -4.8
Mid 15……242 41.0 41.2 41.6 43.1…..   0.01…  2.1
Low 15……..73 43.5 42.6 42.7 43.7….. 0.11…. 0.2
Dem>50% 935 67.3 65.2 62.7 60.8.. -0.35… -6.5

HISTORICAL PRESIDENTIAL EXIT POLLS

A comprehensive analysis of 274 unadjusted 1988-2008 state and 6 national presidential exit polls proved systemic election fraud. The Democrats led the recorded vote by 48-46%, but led the exit polls by a whopping 52-42%. The True Vote Model matched and therefore confirmed the exit polls.

The Adjusted 2004 National Exit Poll indicated that 52.6 million of 2004 voters (43%) were returning Bush 2000 voters and just 37% were returning Gore voters. But this is impossible since Bush had just 50.5 million votes in 2000. Approximately 2 million died and 1 million did not return to vote in 2004. Therefore 5 million phantom Bush voters were required in order to match the recorded vote. Recall that Gore won the popular recorded vote by 540,000 (he actually won by 3-5 million True Votes). The exit pollsters switched 471 (6.7%) of Kerry’s 7,064 responders (of 13660 polled) to Bush.

The Adjusted 2008 National Exit Poll indicated that 60 million (46%) of the 131 million who voted in 2008 were returning Bush 2004 voters and just 49 million (37%) were returning Kerry voters. In other words, in order to match the 2008 recorded vote, there had to be 12 million more returning Bush 2004 voters than returning Kerry voters. But Bush won the bogus 2004 recorded vote by just 3 million! Kerry won the True Vote by close to 10 million. He won the unadjusted state and national exit polls by 6 million. Therefore Obama won the True Vote in 2008 by 22 million, not the 9.5 million recorded.

The pattern is clear. It’s not even close.

An excellent paper from mathematician Kathy Dopp:
http://electionmathematics.org/em-audits/US/2014/USElections2014.pdf

TRACK RECORD
Election Model Forecast; Post-election True Vote Model

1988-2008 State and National Presidential True Vote Model https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdGN3WEZNTUFaR0tfOHVXTzA1VGRsdHc#gid=0

1968-2012 National Presidential True Vote Model https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdFpDLXZmWUFFLUFQSTVjWXM2ZGtsV0E#gid=4

2004 (2-party vote shares)
Model: Kerry 51.8%, 337 EV (snapshot)
https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdGN3WEZNTUFaR0tfOHVXTzA1VGRsdHc#gid=0
State exit poll aggregate: 51.7%, 337 EV
Recorded Vote: 48.3%, 255 EV
True Vote Model: 53.6%, 364 EV

2008
Model: Obama 53.1%, 365.3 EV (simulation mean) http://www.richardcharnin.com/2008ElectionModel.htm
Recorded: 52.9%, 365 EV
State exit poll aggregate: 58.0%, 420 EV
True Vote Model: 58.0%, 420 EV

2012 (2-party state exit poll aggregate shares)
Model: Obama 51.6%, 332 EV (Snapshot) https://richardcharnin.wordpress.com/2012/10/17/update-daily-presidential-true-voteelection-fraud-forecast-model/
Recorded : 51.6%, 332 EV
True Vote Model: 55.2%, 380 EV

 

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