[A math legend just died. He literally reinvented aspects of modern math.] [News Republic]

http://www.newsrepublic.net/detail/05A6AAE69910100001_us?pid=14&referrer=200620&showall=1&mcc=310

# Category Archives: Mathematics

# How to improve your math skills

How to improve your math skills?

This article is from Time Inc. It can be helpful for young adults. It talks about math anxiety and related issues.

http://time.com/4970465/how-to-improve-math-class/

# To Live Your Best Life; Do Mathematics- By Kevin Hartnett

* (The ancient Greeks argued that the best life was filled with beauty, truth, justice, play and love. The mathematician Francis Su knows just where to find them*.)

Math conferences don’t usually feature standing ovations, but Francis Su received one last month in Atlanta. Su, a mathematician at Harvey Mudd College in California and the outgoing president of the Mathematical Association of America (MAA), delivered an emotional farewell address at the Joint Mathematics Meetings of the MAA and the American Mathematical Society in which he challenged the mathematical community to be more inclusive.

Su opened his talk with the story of Christopher, an inmate serving a long sentence for armed robbery who had begun to teach himself math from textbooks he had ordered. After seven years in prison, during which he studied algebra, trigonometry, geometry and calculus, he wrote to Su asking for advice on how to continue his work. After Su told this story, he asked the packed ballroom at the Marriott Marquis, his voice breaking: “When you think of who does mathematics, do you think of Christopher?”

Su grew up in Texas, the son of Chinese parents, in a town that was predominantly white and Latino. He spoke of trying hard to “act white” as a kid. He went to college at the University of Texas, Austin, then to graduate school at Harvard University. In 2015 he became the first person of color to lead the MAA. In his talk he framed mathematics as a pursuit uniquely suited to the achievement of human flourishing, a concept the ancient Greeks called *eudaimonia*, or a life composed of all the highest goods. Su talked of five basic human desires that are met through the pursuit of mathematics: play, beauty, truth, justice and love.

If mathematics is a medium for human flourishing, it stands to reason that everyone should have a chance to participate in it. But in his talk Su identified what he views as structural barriers in the mathematical community that dictate who gets the opportunity to succeed in the field — from the requirements attached to graduate school admissions to implicit assumptions about who looks the part of a budding mathematician.

When Su finished his talk, the audience rose to its feet and applauded, and many of his fellow mathematicians came up to him afterward to say he had made them cry. A few hours later *Quanta Magazine* sat down with Su in a quiet room on a lower level of the hotel and asked him why he feels so moved by the experiences of people who find themselves pushed away from math. An edited and condensed version of that conversation and a follow-up conversation follows.Mark Skovorodko for Quanta Magazine

*QUANTA MAGAZINE: The title of your talk was “Mathematics for Human Flourishing.” Flourishing is a big idea — what do you have in mind by it?*

FRANCIS SU: When I think of human flourishing, I’m thinking of something close to Aristotle’s definition, which is activity in accordance with virtue. For instance, each of the basic desires that I mentioned in my talk is a mark of flourishing. If you have a playful mind or a playful spirit, or you’re seeking truth, or pursuing beauty, or fighting for justice, or loving another human being — these are activities that line up with certain virtues. Maybe a more modern way of thinking about it is living up to your potential, in some sense, though I wouldn’t just limit it to that. If I am loving somebody well, that’s living up to a certain potential that I have to be able to love somebody well.

*And how does mathematics promote human flourishing?*

It builds skills that allow people to do things they might otherwise not have been able to do or experience. If I learn mathematics and I become a better thinker, I develop perseverance, because I know what it’s like to wrestle with a hard problem, and I develop hopefulness that I will actually solve these problems. And some people experience a kind of transcendent wonder that they’re seeing something true about the universe. That’s a source of joy and flourishing.

Math helps us do these things. And when we talk about teaching mathematics, sometimes we forget these larger virtues that we are seeking to cultivate in our students. Teaching mathematics shouldn’t be about sending everybody to a Ph.D. program. That’s a very narrow view of what it means to do mathematics. It shouldn’t mean just teaching people a bunch of facts. That’s also a very narrow view of what mathematics is. What we’re really doing is training habits of mind, and those habits of mind allow people to flourish no matter what profession they go into.

*Several times in your talk you quoted Simone Weil, the French philosopher (and sibling of the famed mathematician Andr**é** Weil), who wrote, “Every being cries out silently to be read differently.” Why did you choose that quote?*

I chose it because it says in a very succinct way what the problem is, what causes injustice — we judge, and we don’t judge correctly. So “read” means “judged,” of course. We read people differently than they actually are.

*And how does that apply to the math community?*

We do this in lots of different ways. I think part of it is that we have a picture of who actually can succeed in math. Some of that picture has been developed because the only examples we’ve seen so far are people who come from particular backgrounds. We’re not used to, for instance, seeing African-Americans at a math conference, although it’s become more and more common.

We’re not used to seeing kids from lower socioeconomic backgrounds in college or grad school. So what I was trying to say is: If we’re looking for talent, why are we choosing for background? If we really want to have a more diverse set of people in mathematical sciences, we have to take into account the structural barriers that make it hard for people from disadvantaged backgrounds to succeed in math.

# ‘Why Unanimity & Too Much Evidence Is A Bad Thing’ By Lisa Zyga

Under ancient Jewish law, if a suspect on trial was unanimously found guilty by all judges, then the suspect was acquitted. This reasoning sounds counterintuitive, but the legislators of the time had noticed that unanimous agreement often indicates the presence of systemic error in the judicial process, even if the exact nature of the error is yet to be discovered. They intuitively reasoned that when something seems too good to be true, most likely a mistake was made.

n a new paper to be published in *The Proceedings of The Royal Society A*, a team of researchers, Lachlan J. Gunn, et al., from Australia and France has further investigated this idea, which they call the “paradox of unanimity.”

“If many independent witnesses unanimously testify to the identity of a suspect of a crime, we assume they cannot all be wrong,” coauthor Derek Abbott, a physicist and electronic engineer at The University of Adelaide, Australia, told *Phys.org*. “Unanimity is often assumed to be reliable. However, it turns out that the probability of a large number of people all agreeing is small, so our confidence in unanimity is ill-founded. This ‘paradox of unanimity’ shows that often we are far less certain than we think.”

**Unlikely agreement**

The researchers demonstrated the paradox in the case of a modern-day police line-up, in which witnesses try to identify the suspect out of a line-up of several people. The researchers showed that, as the group of unanimously agreeing witnesses increases, the chance of them being correct decreases until it is no better than a random guess.

In police line-ups, the systemic error may be any kind of bias, such as how the line-up is presented to the witnesses or a personal bias held by the witnesses themselves. Importantly, the researchers showed that even a tiny bit of bias can have a very large impact on the results overall. Specifically, they show that when only 1% of the line-ups exhibit a bias toward a particular suspect, the probability that the witnesses are correct begins to decrease after only three unanimous identifications. Counterintuitively, if one of the many witnesses were to identify a different suspect, then the probability that the other witnesses were correct would substantially increase.

The mathematical reason for why this happens is found using Bayesian analysis, which can be understood in a simplistic way by looking at a biased coin. If a biased coin is designed to land on heads 55% of the time, then you would be able to tell after recording enough coin tosses that heads comes up more often than tails. The results would not indicate that the laws of probability for a binary system have changed, but that this particular system has failed. In a similar way, getting a large group of unanimous witnesses is so unlikely, according to the laws of probability, that it’s more likely that the system is unreliable.

The researchers say that this paradox crops up more often than we might think. Large, unanimous agreement does remain a good thing in certain cases, but only when there is zero or near-zero bias. Abbott gives an example in which witnesses must identify an apple in a line-up of bananas—a task that is so easy, it is nearly impossible to get wrong, and therefore large, unanimous agreement becomes much more likely.

On the other hand, a criminal line-up is much more complicated than one with an apple among bananas. Experiments with simulated crimes have shown misidentification rates as high as 48% in cases where the witnesses see the perpetrator only briefly as he runs away from a crime scene. In these situations, it would be highly unlikely to find large, unanimous agreement. But in a situation where the witnesses had each been independently held hostage by the perpetrator at gunpoint for a month, the misidentification rate would be much lower than 48%, and so the magnitude of the effect would likely be closer to that of the banana line-up than the one with briefly seen criminals.

Read more at: http://phys.org/news/2016-01-evidence-bad.html#jCp

posted by f.sheikh