In our previous post, we have approximated the dependence of the number of polling stations on the portion of United Russia at a given polling station. Now we can estimate the number of votes falsified by UR from simple functional dependences obtained in the post, i.e. the expected normal distribution and the sine function after 29%.
Let’s take one polling station with, say, 60% in favor of UR. The mean value estimated from the normal distribution is 29%. Therefore, the expected value is 29% as well and the portion of likely falsified votes in 31%. Here we disregard the falsification technique. It can be redistribution of votes from other parties or direct adding of faked votes to the correct result. In any case, 31% of the total number is wrongly assigned to UR. For a middle size polling station of, say, 1000 people it makes 310 wrong votes. Our estimate of the number of polling stations between 60% and 61% is 1160. (Notice that the original bins were only 0.5%-wide.) Hence, there are 1160x310=360000 wrong votes altogether. In the range between 29% and 30%, the difference between the normal and sine distribution are small and the number of wrong votes is only 600. In the range between 99% and 100%, one has 472000 votes hacked.
Summing all bins up one obtains 20,000,000 votes biasing the elections outcome. Same as estimated initially using very crude approximations.