That's my point. The Edison data (the data that goes to the SOS of each state and is used to certify the elections) does not show that. The CALCULATION shows that.
Let me illustrate from a pretend entry from the NYT scrap data (again, the data set I believe this "analyst" used):
Date: 11/4/2020 12:00:00
Total Votes: 1,630,257
Biden Percent: .666
Trump Percent: .334
Other Percent: .000
Then, when you go to calculate the "Trump votes" and "Biden Votes" you get:
Biden Votes = 1,630,257 * 0.666 = 1,085,751.162
Trump Votes = 1.630,257 * 0.334 = 544,505.838
These calculations produce decimals (3 decimal point because that's how multiplication works). But that's not the real number being reported from the Dominion Servers to Edison (and presumably the SOS's).
The Edison data for such an entry would look something like:
Biden Vote: 1,086,129
Trump Vote: 544,128
These numbers not only don't have decimal places, but they aren't even the same number. The reason for this is one is reported (the Edison data) and the other is Calculated by multiplying a whole number (1,630,257) by a decimal accurate to the thousandths place (.666 e.g.).
The error value from such a calculation MUST be carried through or you get crappy analysis. In this case the real number from the Biden calculation is:
1,630,257 * 0.666 = 1,085,751.162 +/- 806.977
This means the REAL value for Biden falls somewhere between:
1,084,936.064 and 1,086,549.988 (which is confirmed in the Edison data).
This mistake was made by many people, not just the Jim Hoft, but he keeps running wild with it, making all kinds of false conclusions (like his "drop and roll" thing). Well, I shouldn't say his conclusions are all false, not all of them are. You don't need the increased precision from the Edison data to come to many of the conclusions, but a lot of his stuff is just plain wrong.
Again, the Edison data shows conclusively that it was NOT random samplings from a biased population (election data). In fact the Edison data shows it BETTER than the NYT .json scrap data.
That's my point. The Edison data (the data that goes to the SOS of each state and is used to certify the elections) does not show that. The CALCULATION shows that.
Let me illustrate from a pretend entry from the NYT scrap data (again, the data set I believe this "analyst" used):
Date: 11/4/2020 12:00:00
Total Votes: 1,630,257
Biden Percent: .666
Trump Percent: .334
Other Percent: .000
Then, when you go to calculate the "Trump votes" and "Biden Votes" you get:
Biden Votes = 1,630,257 * 0.666 = 1,085,751.162
Trump Votes = 1.630,257 * 0.334 = 544,505.838
These calculations produce decimals (3 decimal point because that's how multiplication works). But that's not the real number being reported from the Dominion Servers to Edison (and presumably the SOS's).
The Edison data for such an entry would look something like:
Biden Vote: 1,086,129
Trump Vote: 544,128
These numbers not only don't have decimal places, but they aren't even the same number. The reason for this is one is reported (the Edison data) and the other is Calculated by multiplying a whole number (1,630,257) by a decimal accurate to the thousandths place (.666 e.g.).
This REAL value from such a calculation MUST be carried through or you get crappy analysis. In this case the real number from the Biden calculation is:
1,630,257 * 0.666 = 1,085,751.162 +/- 806.977
This means the REAL value for Biden falls somewhere between:
1,084,936 and 1,086,550 (which is confirmed in the Edison data).
This mistake was made by many people, not just the Jim Hoft, but he keeps running wild with it, making all kinds of false conclusions (like his "drop and roll" thing). Well, I shouldn't say his conclusions are all false, not all of them are. You don't need the increased precision from the Edison data to come to many of the conclusions, but a lot of his stuff is just plain wrong.
Again, the Edison data shows conclusively that it was NOT random samplings from a biased population (election data). In fact the Edison data shows it BETTER than the NYT .json scrap data.