Dr. Shiva has a critic

Actually, Matthew Parker is far from incompetent. Let me be very clear, I voted for Donald Trump in both 2016 and 2020; however, your name calling and ad hominem attacks do not a valid argument make.
Like Dr. Shiva and his colleagues, I am also an engineer with more than 25 years of software development and data analysis experience, and I can definitively state that Mattt’s simple algebraic assessment of the the artificial gradient modification demonstrates the fallacy in Dr. Shiva’s analysis: the correlations between raw data (x-axis) and normalized data (y-axis) are not definitive proof of fraud. In fact, as Matt Parker derived, the following equation
(y-x)=(m-1)x+b
can be further manipulated to apply any arbitrary slope by changing the “1” to a variable as follows:
(y-x)=(m-a)x+b
Thus, the slope of Dr. Shiva’s “correlation” can represent any line in quadrant 1 and 4 of the x-y plane by varying a from negative infinity to positive infinity.
If you don’t believe me, then you need to find someone, whom you trust, with a fundamental understanding of basic highschool-level linear algebra and curve fitting techniques.
Do I believe that election fraud did not occur? THe answer is unequivocally, “NO.” However, the election data analysis by Dr. Shiva and his colleagues is flawed, and its promotion as unassailable truth is equally fraudulent.
In short, I have not yet seen any data and/or analysis that proves that the fraud, which I believe occurred, actually occurred. However, my beliefs and suspicions are not valid forms of proof … and neither are anyone else’s.