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On Elections in Syria
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/ Categories: Syria, Reverse Engineering

On Elections in Syria

The election results in Syria are just as fabricated as those in Luhansk.

Roman Tumaykin discovered that the election results in Syria are as fabricated as those in Luhansk.


They also calculated the number of voters based on predetermined percentages. Moreover, they were so careless that they failed to notice that the sum of votes for all candidates, invalid ballots, and the total number of "voters" do not match! The discrepancy (one person) is precisely the kind of error that occurs when one is rounding percentages, which exposes them completely. Even in Dagestan, this didn't happen!


Roman's text from Facebook:


Recently, I read a post by Alexei Kopylov about the conclusions that a meticulous mathematician can draw from election data, such as the elections in Ukraine’s Donetsk region. To summarize: when a hypothetical election official is told to fabricate a certain percentage, they simply take a calculator and multiply the number of voters by the desired percentage to arrive at the final numbers. The result is a suspiciously neat outcome — the number of votes is accurate to the unit or tens of people, even though each percentage point could represent tens or hundreds of thousands of individuals.

As someone with a background in mathematics, a former bureaucrat, and now a programmer, I decided to analyze the official election results in Syria.


Here are the given numbers (http://sana.sy/eng/393/2014/06/04/548613.htm):

Total eligible voters: 15,845,575
Votes cast: 11,634,412
Invalid ballots: 442,108 (3.8%)
For Assad: 10,319,723 (88.7%)
For Al-Nouri: 500,279 (4.3%)
For Hajar: 372,301 (3.2%)
The voter turnout percentage is 73.4237287%, which seems plausible.
But then, the anomalies begin.
Firstly, note that one-tenth of a percent of voters equals 11,634 people.

The number of invalid ballots (rounded to the nearest whole number) is EXACTLY 3.8% of the total votes cast: 11,634,412 * 0.038 = 442,107.656, which rounds to 442,108.
Votes for Assad (rounded to the nearest whole number) are EXACTLY 88.7% of the total votes cast: 11,634,412 * 0.887 = 10,319,723.44, which rounds to 10,319,723.
Votes for Al-Nouri (rounded to the nearest whole number) are EXACTLY 4.3% of the total votes cast: 11,634,412 * 0.043 = 500,279.716, which rounds to 500,280, though this differs by one person from the official result, possibly due to a calculator error.
Votes for Hajar (rounded to the nearest whole number) are EXACTLY 3.2% of the total votes cast: 11,634,412 * 0.032 = 372,301.184, which rounds to 372,301.
Adding up all these figures (442,108 + 10,319,723 + 500,279 + 372,301) gives 11,634,411, which is one less than the officially announced total. This indicates that they did not calculate the results by summing the votes, but rather distributed the votes by multiplying the number of voters by the predetermined percentages.

Probability theory is disgraced and humiliated. In one election, there were four events, each with a probability of 1/11,634, or 0.008595%.

In other words, roughly 9 thousandths of a percent! And the probability of all four events happening simultaneously is 0.000000000000005459%

Draw your own conclusions.

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Articles on the Elections

Azat Gabdulvaleev "Analysis of election results in the city of Grozny using graphical visualization and turnout counting based on video recordings from polling stations"

Presentation at the II Round Table of Mathematicians

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Azat Gabdulvaleev "Analysis of election results in the city of Grozny using graphic visualization and turnout counting based on video recordings from polling stations

The subject of the study is the capital of the Chechen Republic - the city of Grozny. It should be said that Chechnya consistently shows superloyal results in elections at any level.

Azat Gabdulvaleev "Graphical visualization of open data as a simple way to detect anomalies in voting results"

Presentation at the II Round Table of Mathematicians

Azat Gabdulvaleev 0 15520

One such method is graphical visualization of open data. There is little or no math involved, but the charts can immediately identify some anomalies and indicate areas that need more detailed investigation.

So you can visualize open data in a graphical way.

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