This video will demonstrate how to measure the difference between a fair and an unfair election, where an unfair election is an election where the result is predetermined algorithmically. At the very core of this article lay the assumption of Causality, that the Effect cannot precede the Cause; likewise, the Aggregate Percentage of a Candidate cannot precede the Election Day and the Mail-in Percentages of that candidate. In a fair election, the aggregate cannot be known until after all ballots are cast; in an election that is unfair, where the aggregate was predetermined, the aggregate becomes the cause and the Mail-in Vote (and/or the Election Day Vote) becomes the effect...and the laws of mathematics allow us to readily discern between which was the cause...and which was the effect. To Paraphrase Immanuel Kant: “The causation is the thing without which, is a condition of possibility of a thing, and so it is satisfied in the thing.” The aggregate is not a condition of possibility for the Mail-in votes number. The Aggregate is a Concept that relates two things. People vote by mail and people vote at the polls on election day, but no one, to my knowledge, has voted by aggregate. The content of this article transcends mere elections, these principles can be applied to detect financial fraud on Wall Street, reveal bogus claims from engineered studies and even to expose an entire body of manufactured evidence to support a scientific hypothesis.