Unfortunately, Dr. shiva's analysis is also flawed. The y-axis needs to be normalized by Repub straight ticket vote for any slope in the curve to be significant. Otherwise, you're just showing that differences in raw percentages grow with the magnitude of the raw percentages, which is self-evident and not a sign of fraud.
t = T/R = ratio of Trump vote to straight ticket Repub
T can therefore also be described by the equation: T = tR
Therefore, the y-axis of Dr. Shiva's graph can be written as: T - R = tR - R = (t - 1)R
In other words, the slope of the graph (t - 1) solely depends on the ratio of Trump vote to straight ticket Repub vote. If that ratio is greater than 1, it will have a positive slope. If that ratio is less than 1, it will have a negative slope. The only time there will be no slope is if that ratio is equal to 1.
Unfortunately, Dr. shiva's analysis is also flawed. The y-axis needs to be normalized by Repub straight ticket vote for any slope in the curve to be significant. Otherwise, you're just showing that differences in raw percentages grow with the magnitude of the raw percentages, which is self-evident and not a sign of fraud.
wrong
I can prove it with algebra if you like.
T = Trump vote pct of total
R = straight ticket Repub vote pct of total vote
t = T/R = ratio of Trump vote to straight ticket Repub
T can therefore also be described by the equation: T = tR
Therefore, the y-axis of Dr. Shiva's graph can be written as: T - R = tR - R = (t - 1)R
In other words, the slope of the graph (t - 1) solely depends on the ratio of Trump vote to straight ticket Repub vote. If that ratio is greater than 1, it will have a positive slope. If that ratio is less than 1, it will have a negative slope. The only time there will be no slope is if that ratio is equal to 1.
I've come back here because I ran across this, to your point: https://youtu.be/aokNwKx7gM8