Recent data from Russia have a dubious lack of variation
That is the conclusion of a new study to be published in, a statistics magazine, by the researcher Dmitry Kobak. Mr Kobak has a penchant for such studies—he previously demonstrated fraud in Russian elections based on anomalous tallies from polling stations. His latest study examines how reported death tolls vary over time. He finds that this variance is suspiciously low in a clutch of countries—almost exclusively those without a functioning democracy or a free press.
This idea can be useful in modelling the number of covid deaths, but requires one extension. Unlike a typical Poisson process, the number of people who die of covid can be correlated from one day to the next—superspreader events, for example, lead to spikes in deaths. As a result, the distribution of deaths should be what statisticians call “overdispersed”—the variance should be greater than the mean.
Yet data from 17 countries had the opposite pattern. In many weeks, the variance of each distribution was less than the mean. This is a statistical smoking gun. “It seems reasonable to conclude that there’s no way these are independent observations,” says David Steinsaltz, a professor of statistics at the University of Oxford.