Posted on 11/05/2020 11:17:39 AM PST by Truthsearcher
I don't know how many of you have heard of Benford's test. It's basically a very easy and simple way to spot fake numbers.
It basically says in an random set of numbers in a base 10 system, the likelihood of each number appearing is
1 30.1%
2 17.6%
3 12.5%
4 9.7%
5 7.9%
6 6.7%
7 5.8%
8 5.1%
9 4.6%
When numbers a totally out of synch with those numbers, you know you're not dealing with completely random numbers and dealing with fake made up numbers.
Now here is graph for the number of votes in each precinct for both Trump and Biden in each precinct in Detroit, Milwaukee and Philadelphia
Notice the top 3 Trump numbers are all in line with the Benford curve, whereas the Biden numbers are ridiculously out of line with Benford's law.
This is how even a cursory look at the data alert you to human made up numbers.
Does this have enough creds to be used in a court setting
Pinging here too
The phrase "naturally-occurring" eliminates man-made numbers like serial numbers, identification numbers, and other numbering systems where systematic alteration of the numbers might be introduced for identification purposes. For example, in a phone number, the first three numbers are a geographical indicator.
Numbers that represent measurements or simple counting are naturally occurring in this definition.
Is that why Benford's law is based on logarithms?
Just kidding. Agree with the comment.
Why is the zero digit not listed?
I would think that would be important.
The Benford info may not be completely reliable, due to small sample size. It’s a lead, however.
Ok, I have figured it out.
It is law governing **leading** digits, therefor this explains why there would be no zero.
“Why is the zero digit not listed?”
It would be for a Benford’s analysis of a second or third digit (and those predictions exist as well), but not for an initial digit, because of course if zero is the first digit in a numerical value, it doesn’t really signify anything and it’s just discarded.
The x-axis is digit 1-9. The y-axis is the frequency that ted digit occurs at the first position of the numbers in the number set. The number set consist of all the tallies reported since 11/3/20 from the indicated voting precincts.
So the X-AXIS values have no physical meaning, they are just the digits 1 - 9. The Y-AXIS is the number of times that the digit appears in the set of measurements. In this case, the measurements are the number of votes for each candidate.
The reason I asked for FReepers with statistical analysis skills to look at this data is that we should be able to see if the distribution of digits in the polling place data is reasonable. In other words, are we really seeing the measurement of the voter's actions, or are we seeing the result of fraudulent activity.
I posted another analysis earlier of what values were present in the last two digits of the precinct data from the 478 precincts in Minneapolis. In that case one would expect a nearly random distribution of values, but the 00 value appears 14 times.
That may be just a statistical fluke, but figuring out the chance of that happening would be a worthwhile effort.
Doing similar basic analysis of data for consistency and reasonableness in contested areas would be a good idea.
You sound like someone who is familiar with statistical analysis, so I urge you to start looking at the raw data published by the various election offices.
At the precinct level the actual count for any candidate has a random component, since the number of eligible voters in any precinct has a random component, and the number who turn out to vote does to.
As one example, I would expect that the turnout percentage by precinct would be a distribution around a mean, and certainly not a fixed, constant value.
The percentage of voters who choose a particular candidate in any precinct should also have some variability.
It is just one tool that may be useful to determine if election results are likely to be legitimate.
At this point any FReeper with data analysis skills who has some extra time should grab some data and start looking to see if it appears legitimate.
Benham should be Benford - I can’t type tonight.
Benhams law just captures the probability phenomenon that populations are log-normally distributed in nature. At least in the natural sciences, this phenomenon is undisputed: with a sufficient sample size of a representative* population, log-normal distributions are expected.
To answer your question, the chance of ANY of these three Biden distributions happening in a representative* population asymptotically approaches zero. Such significant deviations from the log-normal distribution (orange bars) are virtually unheard of in nature UNLESS the population has been manipulated. That Bidens data in ALL three of these cities fails to follow inarguable statistical distributions found everywhere in nature is a HUGE red flag to me that fraud is unequivocally present.
Does anyone have the raw data used to produce these plots? The meaning of the binning is still fuzzy. I really dont understand your statement that the measurements (Y axis) are the number of votes for each candidate. Simplifying bin 1 of the Biden Milwaukee plot, does it mean Biden got 1 vote in 60% of precincts when he should have only received 1 vote in 40% of them??
Benham...Benford...
Per the description I received, the y-axis value in Bin 1 is the percentage of precincts across that state where the vote tally started with a “1”.
The analysis just looks at the reported numerical values for each precinct. As an example, if precinct A reported 1200 votes for President Trump, and 3900 votes for Joe Biden, the size of the bar in the chart for President Trump for an X value of 1 would increase by 1 unit.
Similarly, in the chart for Joe Biden, the size of the bar in that chart with an X value of 3 would increase by one unit.
The analysis just looks at a set of numbers to see how they relate to an expected pattern found in many instances. The original physical meaning of the data is unimportant.
To see a graphical presentation of data and say the original meaning of it is unimportant is horrifying. This is how the media bamboozles data-ignorant America with plots, charts, and other half-baked statistics (exhibit A: everything related to COVID). Understanding WHAT is being captured in any graphic is extremely important, both for validating the legitimacy of the graphic (and its conclusions) and for being able to explain it to others.
For instance, a log-normal distribution IDENTICAL to the ones were talking about here could be created by plotting the birthdates of each precinct/ward captain using this bar chart distribution plotting method (except with bins 1-12). That data is obviously utterly meaningless, but the chart would tell the exact same story (at least as the honest Trump plots). Point being, WHAT is being plotted absolutely cannot be ignored. Trust but verify as someone famous once said, especially with pretty pictures.
Stepping down from my angry scientist soapbox (sorry), I now understand what is going on here, and the results are extremely compelling. I would like to know how many total data points there are, which I think would equal the total number of precincts/wards in each of the three cities. Curious if were talking tens or hundreds (probably not thousands) of individual election results. The more data points the stronger the evidence of fraud.
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