I'm writing this in response to the originator of this thread @beedeebeedee[1]. I'm posting it as a top-level comment because I believe it's applicable to the overall conversation.
> According to the theory, in fair elections, turnout indicators typically follow a regular graphical representation that resembles a bell shape. If anomalies appear in the data -- for example, forms different from the bell shape or the bell "grows a tail" -- this indicates unfair elections.
There is *no* respectable statistician who would *ever* draw a conclusion from data. You could say 'may indicate evidence of unfair elections,' but it is impossible to deem whether something occurred or not with 100% certainty.
Now to address their "indicators."
> While in cities the data representation mostly follows a bell shape, in the regions it is anomalously deviated
All statistics is just a representation of data, it tells us nothing of logic. Logic is also based in axioms and it's important to identify what those are.
Here the author is saying the data is "anomalously deviated" with the axiomatic assumption that all voters must follow the same distribution, but why should this assumption be held true? It ignores other logical factors that may sway these distributions.
If I'm a candidate for a political position that would give a rural precinct free money, wouldn't that heavily affect that population's voting outcomes? Surely what's said in a political campaign can sway these things, yet there's nothing in the article that mentions that.
> According to the theory, if a number of stations emerge where one candidate -- the "beneficiary" -- is unusually high, this might indicate falsification. There's a high risk of manipulation where increased overall voter turnout is reflected only in support of the "beneficiary."
So the belief is that because there are 2 distributions for the number of precincts with a certain percentage of "yes" votes, that automatically "indicates falsification"? There needs to be more information than this to make a conclusion. What one holds as axioms are a matter of opinion.
The only way to get something useful out of a counterargument to this is for a proponent to exhaustively list all the votes they think are legitimate, and for the opponent to show the same patterns can occur there as well.
Similarly for a proponent to convince detractors, they'd have to show that other elections they see as legitimate *never* indicate those patterns. Otherwise this is just an opinion piece on data.
> There is no respectable statistician who would ever draw a conclusion from data.
This is outright pedantry, but I'm willing to give the benefit of the doubt. Scientific research is literally the process of drawing conclusions from data, after repeated measurement and control of independent variables.
No benefit of the doubt is needed, I made a true statement, albeit a subjective one about who I consider "respectable".
To me, statisticians analyze data and make objective statements about what they see. The process of scientific research is a different beast altogether. The objective statements about the data can only be used to inspire or support an argument. The correctness of the argument can only be recognized if the listener is convinced.
I'm not sure I follow your idea that correctness emerges from belief, but that could get epistemological quickly.
What I can address is that the role of a statistician is to interpret the statements made by data towards the objective (an unobtainable notion), not vice versa. I don't know any statistician, myself included, who isn't aware of the limitations of sampling, and thus the impossibility of dealing in objectivity -- hence why conclusions are often posited in speculative terms, such as probabilities or even hypotheses. Having the ability to reach those conclusions from the recorded observations of real phenomena is why statisticians tend to operate within subject matters.
Towards that end, I do agree that any statistician worth their salt would not take too much at face value on a two dimensional chart, and that this whole matter bears more investigation. But the idea that no respectable statisticians draw conclusions from data... I'm left to assume that you respect no statisticians.
Hi derangedHorse, thanks for your insight. The anomaly is that there appears to be a heavy shift in votes only in (1) early voting, and not in (2) mail-in ballots or (3) Election Day voting. Additionally, the anomaly only appears for all tabulators after 300 or more votes are cast.
> There is no respectable statistician who would ever draw a conclusion from data. You could say 'may indicate evidence of unfair elections,' but it is impossible to deem whether something occurred or not with 100% certainty.
The originators of the analysis are claiming that this indicates manipulation. Perhaps they should have given more qualifiers in that image of their analysis, but the data is alarming and it is an up-hill battle even to get their analysis noticed (other than the press release to WCIA, only Newsweek has mentioned it). We can say 'maybe' but given the current political and media environment right now, it is likely that that qualification would have doomed their analysis from getting any coverage at all.
Here is a video from the group that discusses these issues and is worth watching because it speaks directly to your concerns and others: https://www.youtube.com/watch?v=WOQ-GxJyJN4
"The pattern above shows an inexplicable spike in vote distribution that is statistically unlikely based on typical human voting behavior."
And while discussing alternate causes ("Deep Red" Areas)
"While such a deviation in the data could potentially still emerge, this does not explain why the pattern is limited to Early Voting, as in that scenario it would be reasonable to expect the same deviation to appear in Election Day results. Instead, Election Day results indicate a normal, expected variation."
6:11 I don't find this particularly strange. I think they'd make a much stronger argument if they showed the drop-off vote for 2020. I found it strange that they only picked 2012 and 2016 given my theory that drop-off votes are probably more prominent in controversial elections. Especially given the fact Kamala entered the race somewhat last minute. I also find it odd that there are no links to explore the previous years that were shown in the video from the website linked in the video's description [1].
10:10 Another claim of irregularity that doesn't quite support their conclusion. It seems they're indicating that both plots seem irregular, which I agree, but there thesis of fraud doesn't completely address 2020's case. They could say republican cheated in 2020 as well, but then they'd have to explain why this election went any different.
11:36 Here they're trying to support the irregularity of the data with anecdote. "Does this match from your opinion with the actual demographic there?" is not a methodical approach to figuring out what's wrong. Surely not every republican would be okay with fraudulent votes regardless of who won. A contrary voice in these video would lend some credence to their claims.
13:28 Voting against one's registered party also doesn't seem crazy to me as I've had many friends who have this past election. My own anecdote doesn't affect the data and may not sway arguments, nor does my theory of controversial elections breeding "irregular" results, but hopefully it can create an equally valid opinion than the one presented in the video.
15:05 If someone was rigging the election in what way? Any security model being claimed as breached needs to define what constitutes a break and how the attack could create that break in security.
16:30 I don't understand why a '2014 Wisonsin Gov. Race' (the title of the graph) is applicable here. Maybe she just used it as a lead-in for the next part?
18:37 Why is she bringing up the random distribution of inadvertent errors?
After spending about an hour watching the video and observing the results, I'm even more skeptical of their claims.
> 6:11 I don't find this particularly strange. I think they'd make a much stronger argument if they showed the drop-off vote for 2020. I found it strange that they only picked 2012 and 2016
It would have been nice to have 2020 there too, but they may not have had access to the data
> 10:10 Another claim of irregularity that doesn't quite support their conclusion. It seems they're indicating that both plots seem irregular, which I agree, but there thesis of fraud doesn't completely address 2020's case. They could say republican cheated in 2020 as well, but then they'd have to explain why this election went any different.
A possible explanation as to why 2020 cheating failed and 2024 did not could be that the cheating was not able to overcome how unpopular he was for his handling of Covid and other issues. For the cheating to work, it cannot be obvious and therefore must be limited. Conversely, Kamala was not as popular in 2024 as Biden was in 2020, so the cheating was successful.
Alternatively, in Trump's own words, Elon made the difference in 2024: "He knows those computers better than anybody. All those computers. Those vote-counting computers," Trump told the crowd. "And we ended up winning Pennsylvania like in a landslide." https://www.newsweek.com/donald-trump-elon-musk-voting-machi...
It could be that whoever was doing the cheating did not have the resources to enact it as successfully without Elon's support (Starlink, Shaotran, etc).
> 11:36 Here they're trying to support the irregularity of the data with anecdote.
> 13:28 Voting against one's registered party also doesn't seem crazy to me
Right, anecdotal evidence and the irregularity of voting against your registered party are not conclusive evidence, but do add to the consensus that a more systematic analysis needs to be done.
> 15:05 If someone was rigging the election in what way? Any security model being claimed as breached needs to define what constitutes a break and how the attack could create that break in security.
That is exactly one of the next steps that should be taken. Figure out how it could have been done, now that there is evidence that points to irregularities. The possibility does not prove it happened, but it would then help go towards the further step of trying to find evidence that it did (once we know where to look and what for).
> 16:30 I don't understand why a '2014 Wisonsin Gov. Race' (the title of the graph) is applicable here. Maybe she just used it as a lead-in for the next part?
She is showing the percentage of the cumulative summation of votes. She has data for the 2014 Wisconsin race that is categorized based on the type of the voting machines. The green line and purple line are relatively flat, showing that the percentage of votes did not change significantly based on the number of cumulative votes. The red lines are suspicious because the percentage grows significantly after a few thousand votes. I'm not sure why they used a line graph instead of a scatterplot, but presumably they fit a line to the data for each machine.
> 18:37 Why is she bringing up the random distribution of inadvertent errors?
She's bringing it up to point out that it could not be caused by random errors (i.e., human errors caused by the election workers, etc), because random errors would be randomly distributed and produce roughly a flat line. The red lines aren't flat, so they are not contributing to the gain in votes.
Look at the graphs at 19:00 and 20:00 for Clark County, NV 2024 early voting. They both show increases in the percentage rate for Trump after around 300 votes for each machine. As one of the speakers says,
"If we're stuffing a bunch of tabulators at 60% for Trump, then we're going to get an asymptote at 60%," which is visible in the data for Clark County, NV in 2024
Thank you for bringing up your points, because after watching the video and with your criticism in mind, addressing them made me more confident that we need a comprehensive investigation to follow this lead. If their claim is correct, it is unlikely that we will see that investigation led by the Federal government, but citizens and states can take the lead.
The real cheating has been in throwing up roadblocks to voting. The Felon didn't win either time, it's just he was successful enough at suppressing Democrat votes that he "won". Since the fraud isn't at the ballot box no examination of the voting will reveal it. Rather, you have to poll the people as to why they didn't vote--didn't want to or were prevented from doing so.
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> According to the theory, in fair elections, turnout indicators typically follow a regular graphical representation that resembles a bell shape. If anomalies appear in the data -- for example, forms different from the bell shape or the bell "grows a tail" -- this indicates unfair elections.
There is *no* respectable statistician who would *ever* draw a conclusion from data. You could say 'may indicate evidence of unfair elections,' but it is impossible to deem whether something occurred or not with 100% certainty.
Now to address their "indicators."
> While in cities the data representation mostly follows a bell shape, in the regions it is anomalously deviated
All statistics is just a representation of data, it tells us nothing of logic. Logic is also based in axioms and it's important to identify what those are.
Here the author is saying the data is "anomalously deviated" with the axiomatic assumption that all voters must follow the same distribution, but why should this assumption be held true? It ignores other logical factors that may sway these distributions.
If I'm a candidate for a political position that would give a rural precinct free money, wouldn't that heavily affect that population's voting outcomes? Surely what's said in a political campaign can sway these things, yet there's nothing in the article that mentions that.
> According to the theory, if a number of stations emerge where one candidate -- the "beneficiary" -- is unusually high, this might indicate falsification. There's a high risk of manipulation where increased overall voter turnout is reflected only in support of the "beneficiary."
So the belief is that because there are 2 distributions for the number of precincts with a certain percentage of "yes" votes, that automatically "indicates falsification"? There needs to be more information than this to make a conclusion. What one holds as axioms are a matter of opinion.
The only way to get something useful out of a counterargument to this is for a proponent to exhaustively list all the votes they think are legitimate, and for the opponent to show the same patterns can occur there as well.
Similarly for a proponent to convince detractors, they'd have to show that other elections they see as legitimate *never* indicate those patterns. Otherwise this is just an opinion piece on data.
[1] https://news.ycombinator.com/item?id=42996898