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Data from: Statistical analysis of the presidential elections in Belarus in 2020

Citation

Cherkas, Sergey (2021), Data from: Statistical analysis of the presidential elections in Belarus in 2020, Dryad, Dataset, https://doi.org/10.5061/dryad.d7wm37q0d

Abstract

Elections in Belarus attract much attention around the world. The election result is declared as a victory of Mr. Lukashenko with 80% votes. It is interesting to give the simplest statistical analysis of this victory. According to Belarus law, protocols of precinct election commissions (PECs) must be posted up just after the election procedure, so that everybody could take a photograph of the protocols. Currently, 1527 of the 5767 protocols of PECs are available in the open access at https://docs.google.com/spreadsheets/d/17aK3JxBTGtzULB0-YZGOF0hJwhuViHO3/edit#gid=84585767. We focus an attention on two arrays of numbers taken from these photographs. Namely, the number Ni  of voters at some polling station and the number Mi of voters for Mr. Lukashenko at the same polling station. These numbers give a possibility to calculate the average percentage of those who voted for Mr. Lukashenko, which turns out to be about 60%. That is, a random sample approximately of ¼ of total number of protocol gives a value that differs at about 20% from the declared total value 80%.  Using Monte-Carlo simulation we have calculated a probability of this event and obtain less than one part in million. Next we have considered  Nand Mi as the random variables and calculate probability distribution functions for Mi/Ni and Mi/<Ni> quantities. First function f(x) is of non Gaussian form and has a maximum at x≈0.6, and, an additional maximum at x≈0.8. Second function f(y) has only one maximum at y≈0.6. One the possible explanations is that the correlation (i.e. maximum) in distribution f(x) at x≈0.8  arises due to artificial trimming of the percentage of those who voted for Lukashenko to 80%  in some polling stations.

Methods

Notebook is for Wolfram Mathematica, version 12. It use smoothed Gaussian kernel to calculate probability distribution functions. Files *.txt contain Ni and Marrays for city of Minsk, ans five regions of Belarus. A notebook DistributionsGenBel.nb calculates probability distribution functions for x=Mi/Ni and y=Mi/<Ni> values. Then it calculates mean values over some random sample from 1527 protocols. 

Usage Notes

The files *.txt have to be in the same directory with the notebook.