White House Press Secretary Kayleigh McEnany on Tuesday evening highlighted an incredible statistic that is included in State of Texas v. Pennsylvania, et. al.
“Expert analysis using a commonly accepted statistical test further raises serious questions as to the integrity of this election,” the lawsuit reads. “The probability of former Vice President Biden winning the popular vote in the four Defendant States—Georgia, Michigan, Pennsylvania, and Wisconsin—independently given President Trump’s early lead in those States as of 3 a.m. on November 4, 2020, is less than one in a quadrillion, or 1 in 1,000,000,000,000,000.”
“The odds of Joe Biden winning all four of those states collectively is less than one in a quadrillion to the fourth power,” it continues.
Chances of Biden winning Pennsylvania, Michigan, Georgia, Wisconsin independently after @realDonaldTrump’s early lead is less than one in a quadrillion:
➡️ 1 in 1,000,000,000,000,000
Chances of him winning collectively is “one in a quadrillion to the 4th power”
Texas v. PA ⬇️ pic.twitter.com/tOlgPdai3r
— Kayleigh McEnany (@kayleighmcenany) December 9, 2020
The lawsuit asks the Supreme Court to block the “unlawful election results” in Georgia, Michigan, Pennsylvania, and Wisconsin.
The analysis comes from Dr. Charles J. Cicchetti, Ph.D, a member of Pacific Economics Group, a senior advisor to Pacific Economics Group Research, and a professor of Economics at the University of Southern California. Justin Grimmer, a professor at Stanford University and a senior fellow at the Hoover Institute, says the claim “is based on an embarrassing and basic error in statistical reasoning.”
You can read Cicchetti’s Declaration in the appendix of the lawsuit here, starting on page 20.
HUGE: Judge Allows Forensic Audit of Dominion Voting Machines in Michigan
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Matt Margolis is the author of Airborne: How The Liberal Media Weaponized The Coronavirus Against Donald Trump, and the bestselling book The Worst President in History: The Legacy of Barack Obama. You can follow Matt on Twitter @MattMargolis
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