46th President of the United States, Joe Biden
Discussion
Gandahar said:
.......Already the Democratic party is blaming the lefties, sorry, progressives, for the poor showing in house. This will give Biden a bit more leeway in choosing his cabinet. This has the knock on effect of a moderate cabinet perhaps assisting with the senate, especially if there are some moderate republicans in there also.
Biden didn't get to be President by being Progressive. He needs to, ever so kindly, put the left wing of his party on the back burner, no matter how they hate that, so that he has 4 years of being able to put his agenda forward without being hamstrung by the , er, checks and balances........
The representatives that supported M4A etc were all voted in, the ones that didnt, well, they didnt!Biden didn't get to be President by being Progressive. He needs to, ever so kindly, put the left wing of his party on the back burner, no matter how they hate that, so that he has 4 years of being able to put his agenda forward without being hamstrung by the , er, checks and balances........
Monkeylegend said:
eharding said:
Monkeylegend said:
MBU
Yep - people who qualify for the PH "most senile act of the month" award really should know better....
Will he ever live it down.
Seventy said:
Cheeses of Nazareth said:
Benfords Law
It’s Benford’s. Anyway, https://www.eipartnership.net/rapid-response/what-...
Not that I expect you to either read nor understand it.
A quick tl:dr for people: Benford's law relies on your data set covering a number of orders of magnitude, meaning you can only expect a strong correlation when used with specific data sets. Using it for polling data is questionable because while there are outlier voting districts that have particularly big or small populations the majority of voting districts are within an order of magnitude of each other.
<><><>
A car based example of Benford's law, just because I'd never heard of it before and am sad enough to consider statistics fun (at times).
Benford's law relies on orders of magnitude, so to use the mileage of cars in the UK as an example... we're looking for the first digit on a car's odometer to trend towards being a low number.
Greater than 100k miles on the clock - Most modern cars are capable of reaching 100k miles but the number of cars that reach 200k is far less and 300k far less still so straight away we have a tendency for the first digit to trend towards a low number.
Greater than 10k miles on the clock - Due to the lower order of magnitude there is going to be much more variance in the first number on the odometer, however if we assume that the longer a car has been on the road the greater the chance that it's gone backwards through a hedge or been lost in a barn, then we should see some minor correlation with Benford's law.
Greater than 1k miles - By this point the first number on the odometer is completely random and there is no correlation with Benford's law.
mybrainhurts said:
So many people cheering for a senile old git and the communist woman who will topple him.
Hard to understand.
Hard to understand is why you post something so asinine. You should change your username to “my comments will make your brain hurt”Hard to understand.
For the adults in the room this link shows where Biden, Trump and Harris stand on the political spectrum
https://www.politicalcompass.org/uselection2020
So Harris is quite a long way right of centre, although slightly more liberal than Biden. To any normal person that doesn’t make her a communist. Although I suspect it might to a Trumpette as truth and measured responses not their forte.
eharding said:
Monkeylegend said:
eharding said:
Monkeylegend said:
MBU
Yep - people who qualify for the PH "most senile act of the month" award really should know better....
Will he ever live it down.
Tartan Pixie said:
Interesting, thanks.
A quick tl:dr for people: Benford's law relies on your data set covering a number of orders of magnitude, meaning you can only expect a strong correlation when used with specific data sets. Using it for polling data is questionable because while there are outlier voting districts that have particularly big or small populations the majority of voting districts are within an order of magnitude of each other.
<><><>
A car based example of Benford's law, just because I'd never heard of it before and am sad enough to consider statistics fun (at times).
Benford's law relies on orders of magnitude, so to use the mileage of cars in the UK as an example... we're looking for the first digit on a car's odometer to trend towards being a low number.
Greater than 100k miles on the clock - Most modern cars are capable of reaching 100k miles but the number of cars that reach 200k is far less and 300k far less still so straight away we have a tendency for the first digit to trend towards a low number.
Greater than 10k miles on the clock - Due to the lower order of magnitude there is going to be much more variance in the first number on the odometer, however if we assume that the longer a car has been on the road the greater the chance that it's gone backwards through a hedge or been lost in a barn, then we should see some minor correlation with Benford's law.
Greater than 1k miles - By this point the first number on the odometer is completely random and there is no correlation with Benford's law.
I work with SPC as part of my job, its a well used and essential quality tool, used globally to analize measured data, and cab show you all sorts of trends that you can use to improve processes.A quick tl:dr for people: Benford's law relies on your data set covering a number of orders of magnitude, meaning you can only expect a strong correlation when used with specific data sets. Using it for polling data is questionable because while there are outlier voting districts that have particularly big or small populations the majority of voting districts are within an order of magnitude of each other.
<><><>
A car based example of Benford's law, just because I'd never heard of it before and am sad enough to consider statistics fun (at times).
Benford's law relies on orders of magnitude, so to use the mileage of cars in the UK as an example... we're looking for the first digit on a car's odometer to trend towards being a low number.
Greater than 100k miles on the clock - Most modern cars are capable of reaching 100k miles but the number of cars that reach 200k is far less and 300k far less still so straight away we have a tendency for the first digit to trend towards a low number.
Greater than 10k miles on the clock - Due to the lower order of magnitude there is going to be much more variance in the first number on the odometer, however if we assume that the longer a car has been on the road the greater the chance that it's gone backwards through a hedge or been lost in a barn, then we should see some minor correlation with Benford's law.
Greater than 1k miles - By this point the first number on the odometer is completely random and there is no correlation with Benford's law.
The examples i have seen of Benfords in this instance, which is not an ideal disrubution, as you described, show that while Trump ans all thee down ticket voting follows tbe rule near enough to be taken as good data, in any given area, the Biden data doesn.
And also, the downticket numbers for Trump and the Rep Senate guys follows within a small percentage across the country, and the Reps did very well, but where Biden had big gains after time, those downticket votes just dont follow, and that is only evident in the battleground cities.
I heard someone say, that if this dataset was presented as an exam question to a University,, if yiu didnt ID it as fraud yiu woukd fail.
These types of data anomalies may be 'explainable' but for them to only occur where they have is more than a little suspicious.
As someone who has audited companies and found falsified data, it should not be hard to find.
And of course, if they go in and it all adds up, its all good, and Creepy Joe will get to sniff his way through as long as Kamala lets him.
Cheeses of Nazareth said:
I work with SPC as part of my job, its a well used and essential quality tool, used globally to analize measured data, and cab show you all sorts of trends that you can use to improve processes.
The examples i have seen of Benfords in this instance, which is not an ideal disrubution, as you described, show that while Trump ans all thee down ticket voting follows tbe rule near enough to be taken as good data, in any given area, the Biden data doesn.
And also, the downticket numbers for Trump and the Rep Senate guys follows within a small percentage across the country, and the Reps did very well, but where Biden had big gains after time, those downticket votes just dont follow, and that is only evident in the battleground cities.
I heard someone say, that if this dataset was presented as an exam question to a University,, if yiu didnt ID it as fraud yiu woukd fail.
These types of data anomalies may be 'explainable' but for them to only occur where they have is more than a little suspicious.
As someone who has audited companies and found falsified data, it should not be hard to find.
And of course, if they go in and it all adds up, its all good, and Creepy Joe will get to sniff his way through as long as Kamala lets him.
Fair enough. If you've got a dataset that's being shared widely enough for people to comment on it then is there any chance of a link and source?The examples i have seen of Benfords in this instance, which is not an ideal disrubution, as you described, show that while Trump ans all thee down ticket voting follows tbe rule near enough to be taken as good data, in any given area, the Biden data doesn.
And also, the downticket numbers for Trump and the Rep Senate guys follows within a small percentage across the country, and the Reps did very well, but where Biden had big gains after time, those downticket votes just dont follow, and that is only evident in the battleground cities.
I heard someone say, that if this dataset was presented as an exam question to a University,, if yiu didnt ID it as fraud yiu woukd fail.
These types of data anomalies may be 'explainable' but for them to only occur where they have is more than a little suspicious.
As someone who has audited companies and found falsified data, it should not be hard to find.
And of course, if they go in and it all adds up, its all good, and Creepy Joe will get to sniff his way through as long as Kamala lets him.
As said I don't work with this stuff on a day to day basis but anything I can dump in excel is ideal.
Love your username by the way, always gives me a chuckle
Cheeses of Nazareth said:
And also, the downticket numbers for Trump and the Rep Senate guys follows within a small percentage across the country, and the Reps did very well, but where Biden had big gains after time, those downticket votes just dont follow, and that is only evident in the battleground cities.
Why is this a problem? This is not evidence of fraud.Electro1980 said:
Why is this a problem? This is not evidence of fraud.
Because statistically it shows irregularity.Rep in the Senate overturned Dem seats, but didnt win the presidency.
So that means that you have people who voted for Biden but did not vote Dem on the rest of the ticket.
Trump numbers follow all over the country pretty much, there does not appear to be much spread between upticket and downticket voting, which is what you would expect , but in the 5 cities where Biden has pulled votes out of nowhere, those people didnt vote for the Dems on the rest of the ticket.
Also add that Trump outperformed in all the major non battleground cities , like NY , and Biden underperformed, in all of these places, but miraculously performed in the places where voter fraud is rife, you can do nothing but draw the conclusion that something doesnt add up.
And that is the beauty of statistics, because the numbers are the numbers , and the pattern they make tell you all you need to know.
https://m.youtube.com/watch?v=u2DRwt6RWyc
This is a bit lenghty, but worth it IMO
I think it shows the process well. The upshot is , if there is nothing going on, there is nothing to see. But this suggests there is , and tells you where to look. Forensic accountancy is an art in itself, the tools are there to see any wrong doing.
And as i , and all the rest have said, where there is no foulplay, the results follow , across all tickets.
As for the poll people, they can be ignored , they are part of the problem, they were wrong last time, they were wrong on Brexit, and they were wrong on the election. They are a tool used by a complicit media. If they werent , then they wouldnt be so far out would they
This is just nonsense. If they're going to add votes to the presidential election why wouldn't they also add votes down ticket???
What this actually suggests is that loads of people who would normally vote republican voted against Trump in the presidential election but reverted to the GOP elsewhere.
What this actually suggests is that loads of people who would normally vote republican voted against Trump in the presidential election but reverted to the GOP elsewhere.
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