# This person is “so confused” by the concept of compound interest

‘I’m so confused.’ I’m a school nurse who took out about $30K in student loans — but over the years they have ballooned up to $96K. How could this even happen and what can I do about it?

March 9, 2022

Question: I’d like to obtain advice on tackling student loan debt. I do not have private loans, and I owe approximately $96,000. **I’m so confused** because initially my loans were less than $30,000, but I think the rest of it comes from interest. I’m not sure what I am looking at with my loans. My loans have been in forbearance, and I want to investigate loan forgiveness options. I am a school nurse and support my family, so my income is limited. Can you provide direction? It would be greatly appreciated.

# CORRECTION: Fact check: Deviation from Benford’s Law does not prove election fraud

**Link to my original post: https://danfromsquirrelhill.wordpress.com/2020/11/07/joe-bidens-votes-violate-benfords-law-mathematics/**

**And here’s the correction, which I have also added to my original post:**

**Fact check: Deviation from Benford’s Law does not prove election fraud**

**By Reuters Staff**

**Social media users have been sharing posts that say a mathematical rule called Benford’s Law provides clear proof of fraud in the U.S. presidential election. However, research papers and academics consulted by Reuters consistently say that deviation from Benford’s Law does not prove election fraud took place.**

**Benford’s law says that in many naturally occurring sets of numbers, the first digits of these numbers (eg. the ‘1’ in ‘15’) are not evenly distributed. Measurements with a lower first digit occur more frequently: 1 is the first digit in a number about 30 percent of the time while 9 begins less than 5 percent of numbers. In certain data sets ranging from rainfall amounts to town populations, the numbers follow a Benford’s Law distribution. Deviation of data from Benford’s law has been examined in areas such as finance to detect if something is not right, for example fraud, mistakes or misstatements (here , here) .**

**The posts, such as those here and here , show graphs that compare candidate’s vote tallies by leading digit to the expected distribution according to Benford’s law in order to contend that Biden’s vote tallies do not follow Benford’s Law but Trump’s do. Posts state that Benford’s law is a test that has been used before to detect fraud (here) . Captions on the posts include, “Joe Biden’s votes violate Benford’s Law”; “It’s easy to win if you cheat”; “Statistically impossible odds […] now MATH doesn’t even agree with their faux victory.”**

**Reuters sought comment from experts regarding these claims.**

**Theodore P. Hill, Professor Emeritus of Mathematics at Georgia Tech, Atlanta, cautioned that regardless of the distribution uncovered, the application of Benford’s Law would not provide definitive evidence that fraud took place.**

**“First, I’d like to stress that Benford’s Law can NOT be used to “prove fraud”,” he told Reuters by email. “It is only a Red Flag test, that can raise doubts. E.g., the IRS has been using it for decades to ferret out fraudsters, but only by identifying suspicious entries, at which time they put the auditors to work on the hard evidence. Whether or not a dataset follows BL proves nothing.”**

**Walter Mebane, Professor at the Department of Political Science and Department of Statistics at the University of Michigan (here) authored a December 2006 article (here) around the application of Benford’s Law to the US presidential election results. The article suggested some limitations of the process, but said in the Abstract: “The test is worth taking seriously as a statistical test for election fraud.”**

**Nevertheless, Mebane’s article also said, in the Discussion: “In any case, the 2BL test on its own should not be considered proof either that election fraud has occurred or that an election was clean. A significant 2BL test result can be caused by complications other than fraud. Some kinds of fraud the 2BL test cannot detect.”**

**On Nov. 9, 2020, in response to “several queries” Mebane published a paper called “Inappropriate Applications of Benford’s Law Regularities to Some Data from the 2020 Presidential Election in the United States” (here). His paper says, “The displays shown at those sources using the first digits of precinct vote counts data from Fulton County, GA, Allegheny County, PA, Milwaukee, WI, and Chicago, IL, say nothing about possible frauds” before examining the reasons behind this statement.**

**“It is widely understood that the first digits of precinct vote counts are not useful for trying to diagnose election frauds,” he writes.**

**Elsewhere, a study called “Benford’s Law and the Detection of Election Fraud”, published in 2011 by Joseph Deckert, Mikhail Myagkov, Professor of Political Science at the University of Oregon (here) and Peter Ordeshook, Professor of Political Science at Caltech (here), found that Benford’s Law was “problematical at best” when applied to elections: “We find that conformity with and deviations from Benford’s Law follow no pattern. […] Its “success rate” either way is essentially equivalent to a toss of a coin, thereby rendering it problematical at best as a forensic tool and wholly misleading at worst.” (here)**

**Dr Jen Golbeck, Professor of the College of Information Studies at the University of Maryland (www.cs.umd.edu/~golbeck/), said in a thread on Twitter (here) that the claims in the social media posts are false, citing the above article. She told Reuters, “There is just not solid evidence that Benford works in elections at all. The results are profoundly mixed. Which means it’s not evidence of anything.”**

**Golbeck points out that the numbers on some graphs being cited by social media users are not even labelled, whilst the law “works on very specific types of numbers”. She added that none of the research that analyzes the Benford Law is as simplistic as the analysis people are posting: instead, research uses “quite advanced statistical techniques”, often looking at the second digits which have their own expected distribution.**

**The specific case of the Milwaukee results was also examined by Professor Boud Roukema of Poland’s Nicolaus Copernicus University. Roukema considered the application of Benford’s Law to the 2009 Iranian elections (arxiv.org/abs/0906.2789) . He told Reuters by email: “A major flaw in applying Benford’s law to the Milwaukee results is that the logarithmic distribution – how many “powers of tens” there are – in the numbers of votes per ward in Milwaukee is very narrow. In other words, half of all the wards have total votes from about 570 to 1200, and the logarithmic average (mean) is about 800.**

**“Biden overall got about 70% of the votes in Milwaukee. So the most likely vote for Biden (in the simplest model, assuming no falsification) in a typical Milwaukee ward is something like 0.7 times 800, which is 560 votes. We expect about half the Biden votes to lie between about 400 and 850 in typical Milwaukee wards.**

**“So the most popular first digit of the votes for Biden should be 5 – the first digit of 560 – and 4s and 6s and 7s should also be reasonably frequent.**

**“This is just what we see in the blue vertical bars in top left figure in the diagram at (here). So Benford’s law reasoning, applied to the real data, shows no reason to suspect fraud here.”**

**The academic and digital research coalition Election Integrity Partnership also cautioned against the conclusion that deviation from Benford’s Law is evidence of election fraud (here). It pointed out that for the law to hold, all numbers must be equally likely to appear and the numbers must span multiple orders of magnitude (eg. Range from 100 to 10,000,000). They say that one of these conditions is not met in the election: “For vote tallies, all numbers are equally likely, but not all states meet the second assumption. In the state of Nevada, Esmeralda County has around 900 people while Clark County has over 2,250,000 people. In the state of Vermont, the bounds are much narrower.”**

**VERDICT**

**False. The degree to which Benford’s Law can be used as an indicator of electoral fraud has been debated by academics, but the application of the rule to the leading digit of local vote tallies is problematic and apparent deviation from the law cannot be used alone to prove electoral fraud, experts say.**

**This article was produced by the Reuters Fact Check team. Read more about our fact-checking work here.**

# Joe Biden’s votes violate Benford’s Law (Mathematics) – CORRECTION: Fact check: Deviation from Benford’s Law does not prove election fraud

**CORRECTION:**

**Fact check: Deviation from Benford’s Law does not prove election fraud**

**By Reuters Staff**

**Social media users have been sharing posts that say a mathematical rule called Benford’s Law provides clear proof of fraud in the U.S. presidential election. However, research papers and academics consulted by Reuters consistently say that deviation from Benford’s Law does not prove election fraud took place.**

**Benford’s law says that in many naturally occurring sets of numbers, the first digits of these numbers (eg. the ‘1’ in ‘15’) are not evenly distributed. Measurements with a lower first digit occur more frequently: 1 is the first digit in a number about 30 percent of the time while 9 begins less than 5 percent of numbers. In certain data sets ranging from rainfall amounts to town populations, the numbers follow a Benford’s Law distribution. Deviation of data from Benford’s law has been examined in areas such as finance to detect if something is not right, for example fraud, mistakes or misstatements (here , here) .**

**The posts, such as those here and here , show graphs that compare candidate’s vote tallies by leading digit to the expected distribution according to Benford’s law in order to contend that Biden’s vote tallies do not follow Benford’s Law but Trump’s do. Posts state that Benford’s law is a test that has been used before to detect fraud (here) . Captions on the posts include, “Joe Biden’s votes violate Benford’s Law”; “It’s easy to win if you cheat”; “Statistically impossible odds […] now MATH doesn’t even agree with their faux victory.”**

**Reuters sought comment from experts regarding these claims.**

**Theodore P. Hill, Professor Emeritus of Mathematics at Georgia Tech, Atlanta, cautioned that regardless of the distribution uncovered, the application of Benford’s Law would not provide definitive evidence that fraud took place.**

**“First, I’d like to stress that Benford’s Law can NOT be used to “prove fraud”,” he told Reuters by email. “It is only a Red Flag test, that can raise doubts. E.g., the IRS has been using it for decades to ferret out fraudsters, but only by identifying suspicious entries, at which time they put the auditors to work on the hard evidence. Whether or not a dataset follows BL proves nothing.”**

**Walter Mebane, Professor at the Department of Political Science and Department of Statistics at the University of Michigan (here) authored a December 2006 article (here) around the application of Benford’s Law to the US presidential election results. The article suggested some limitations of the process, but said in the Abstract: “The test is worth taking seriously as a statistical test for election fraud.”**

**Nevertheless, Mebane’s article also said, in the Discussion: “In any case, the 2BL test on its own should not be considered proof either that election fraud has occurred or that an election was clean. A significant 2BL test result can be caused by complications other than fraud. Some kinds of fraud the 2BL test cannot detect.”**

**On Nov. 9, 2020, in response to “several queries” Mebane published a paper called “Inappropriate Applications of Benford’s Law Regularities to Some Data from the 2020 Presidential Election in the United States” (here). His paper says, “The displays shown at those sources using the first digits of precinct vote counts data from Fulton County, GA, Allegheny County, PA, Milwaukee, WI, and Chicago, IL, say nothing about possible frauds” before examining the reasons behind this statement.**

**“It is widely understood that the first digits of precinct vote counts are not useful for trying to diagnose election frauds,” he writes.**

**Elsewhere, a study called “Benford’s Law and the Detection of Election Fraud”, published in 2011 by Joseph Deckert, Mikhail Myagkov, Professor of Political Science at the University of Oregon (here) and Peter Ordeshook, Professor of Political Science at Caltech (here), found that Benford’s Law was “problematical at best” when applied to elections: “We find that conformity with and deviations from Benford’s Law follow no pattern. […] Its “success rate” either way is essentially equivalent to a toss of a coin, thereby rendering it problematical at best as a forensic tool and wholly misleading at worst.” (here)**

**Dr Jen Golbeck, Professor of the College of Information Studies at the University of Maryland (www.cs.umd.edu/~golbeck/), said in a thread on Twitter (here) that the claims in the social media posts are false, citing the above article. She told Reuters, “There is just not solid evidence that Benford works in elections at all. The results are profoundly mixed. Which means it’s not evidence of anything.”**

**Golbeck points out that the numbers on some graphs being cited by social media users are not even labelled, whilst the law “works on very specific types of numbers”. She added that none of the research that analyzes the Benford Law is as simplistic as the analysis people are posting: instead, research uses “quite advanced statistical techniques”, often looking at the second digits which have their own expected distribution.**

**The specific case of the Milwaukee results was also examined by Professor Boud Roukema of Poland’s Nicolaus Copernicus University. Roukema considered the application of Benford’s Law to the 2009 Iranian elections (arxiv.org/abs/0906.2789) . He told Reuters by email: “A major flaw in applying Benford’s law to the Milwaukee results is that the logarithmic distribution – how many “powers of tens” there are – in the numbers of votes per ward in Milwaukee is very narrow. In other words, half of all the wards have total votes from about 570 to 1200, and the logarithmic average (mean) is about 800.**

**“Biden overall got about 70% of the votes in Milwaukee. So the most likely vote for Biden (in the simplest model, assuming no falsification) in a typical Milwaukee ward is something like 0.7 times 800, which is 560 votes. We expect about half the Biden votes to lie between about 400 and 850 in typical Milwaukee wards.**

**“So the most popular first digit of the votes for Biden should be 5 – the first digit of 560 – and 4s and 6s and 7s should also be reasonably frequent.**

**“This is just what we see in the blue vertical bars in top left figure in the diagram at (here). So Benford’s law reasoning, applied to the real data, shows no reason to suspect fraud here.”**

**The academic and digital research coalition Election Integrity Partnership also cautioned against the conclusion that deviation from Benford’s Law is evidence of election fraud (here). It pointed out that for the law to hold, all numbers must be equally likely to appear and the numbers must span multiple orders of magnitude (eg. Range from 100 to 10,000,000). They say that one of these conditions is not met in the election: “For vote tallies, all numbers are equally likely, but not all states meet the second assumption. In the state of Nevada, Esmeralda County has around 900 people while Clark County has over 2,250,000 people. In the state of Vermont, the bounds are much narrower.”**

**VERDICT**

**False. The degree to which Benford’s Law can be used as an indicator of electoral fraud has been debated by academics, but the application of the rule to the leading digit of local vote tallies is problematic and apparent deviation from the law cannot be used alone to prove electoral fraud, experts say.**

**This article was produced by the Reuters Fact Check team. Read more about our fact-checking work here.**

Joe Biden’s votes violate Benford’s Law (Mathematics)

Author: River|Himalaya Scholars

November 7, 2020

As the vote counting for the 2020 Presidential Election continues, various facts suggest rampant frauds in Joe Biden’s votes. So does mathematics in terms of the votes from precincts.

Benford’s law or the first-digit law, is used to check if a set of numbers are naturally occurring or manually fabricated. It has been applied to detect the voting frauds in Iranian 2009 election and various other applications including forensic investigations.

This is what described by Wikipedia:

*“Benford’s law, or the first-digit law, is an observation about the frequency distribution of leading digits in many real-life sets of numerical data. The law states that in many naturally occurring collections of numbers, the leading digit is likely to be small.*

*For example, in sets that obey the law, the number 1 appears as the leading significant digit about 30% of the time, while 9 appears as the leading significant digit less than 5% of the time. If the digits were distributed uniformly, they would each occur about 11.1% of the time. Benford’s law also makes predictions about the distribution of second digits, third digits, digit combinations, and so on.”*

One of the examples is the population of the world, which are naturally occurring numbers.

Distribution of first-digit (in %) of population numbers in 237 countries in 2010.

A number of people on the internet have checked the votes (precinct by precinct) of Joe Biden, Donald Trump as well as other candidates for their legitimacy in terms of the Benford’s Law.

According a Reddit user, r/dataisbeautiful’s calculation, the ‘normal’ distribution of first digits for the different candidates based on Benford’s law is illustrated below.

Youtuber Nyar has shared the observations on a number of counties, concluding that Trump and others’ votes have natural distribution but not for Joe Biden’s.

In Fulton County, Georgia, which overlaps with the Atlantic metropolitan where Joe Biden is expected to win, all of the three candidates have normal distributions for their votes. (Joe Biden 72.6%, Donald Trump 26.2%, Jo Jorgensen 1.2%.)

In Miami-Dade County of Florida, which includes the Miami metropolitan where Joe Biden is expected to win, all candidates’ votes obey Benford’s Law. (Joe Biden 53.4%, Donald Trump 46.1%, Jo Jorgensen 0.3%.)

However, in the Milwaukee County of Wisconsin, which is in one of the key swing states, Joe Biden’s votes violate Benford’s Law while other candidates’ don’t. (Joe Biden 69.4%, Donald Trump 29.4%, Jo Jorgensen 0.9%.)

And in Chicago of Illinois, Joe Biden’s votes are abnormal.

So does that of Allegheny of Pennsylvania which includes Pittsburgh. (Joe Biden 59.0%, Donald Trump 39.9%, Jo Jorgensen 1.2%.)

It looks like maybe Biden had lost big cities like Chicago and Pittsburgh, which is why the fraudulent votes need to be brought in, which skew his curve away from a normal looking one.

For those who are interested to reproduce the analysis, you can follow the instructions here and give it a go.

Author: River|Himalaya Scholars

# Academic journal caves in to social justice warriors who demanded censorship of a scientific paper

This is first paragraph of wikipedia’s article on something known as the “variability hypothesis”

*https://en.wikipedia.org/wiki/Variability_hypothesis*

*Variability hypothesis*

*The variability hypothesis , also the Greater Male Variability Hypothesis, is the hypothesis that males display greater variability in traits than females do. It has often been discussed in relation to cognitive ability, where it has been observed that human males are more likely than females to have very high or very low intelligence. The sex-difference in the variability of intelligence has been discussed since at least Charles Darwin. Sex-differences in variability are present in many abilities and traits – including physical, psychological and genetic ones. It is not only found in humans but in other sexually-selected species as well.*

Either the variability hypothesis is true, or it is false.

The only way to know is to do research.

On August 28, 2018, Theodore P. Hill, a retired professor of mathematics at Georgia Institute of Technology, published a scientific paper titled “An Evolutionary Theory for the Variability Hypothesis,” which supported the variability hypothesis.

The paper has been put online here: https://arxiv.org/pdf/1703.04184.pdf

And here is an archive of that same link: https://web.archive.org/web/20180910143245/https://arxiv.org/pdf/1703.04184.pdf

Social justice accused an academic journal of sexism for publishing the paper. The journal acted very cowardly and has since rescinded the publication. Since the journal still owns the copyright, other academic journals are not allowed to publish it.

Censoring the paper has caused it to become far more popular than it otherwise would have been. Apparently, social justice warriors either don’t know about, don’t care about, or don’t understand the Streisand effect.

# Casino sues winning gamblers and card manufacturer because casino employees did not shuffle the cards

This casino is suing the card manufacturer, and the players who won lots of money, because the casino’s employees didn’t shuffle the cards, which allowed the players to win 41 times in a row.

This has got to be about the most ridiculous lawsuit that I have ever heard about. Yes, I realize there are quite a few contenders in that contest, but this one is even dumber than the other dumb ones… I think.

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