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On Media Coverage of Math
Edited by Mike Breen and Annette Emerson, AMS Public Awareness Officers
Tim Chartier, Davidson College, using math to explore NCAA Tournament Bracketology (Photo by Laura McHugh, MAA)
"The news should start with mathematics, then poetry, and move down from there," from The Humans, by Matt Haig.
See also: The AMS Blog on Math Blogs: Two mathematicians tour the mathematical blogosphere. Editors Brie Finegold and Evelyn Lamb, both PhD mathematicians, blog on blogs that have posts related to mathematics research, applied mathematics, mathematicians, math in the news, mathematics education, math and the arts and more. Recent posts: "Awesome K-12 Math Teachers Exist! And they have blogs," "Geometry and the Imagination," and "On Teaching Analysis."
Maybe it was the title, "Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance," that grabbed the attention of the Financial Times and Bloomberg News. FT's Stephen Foley writes that the authors of the article in May Notices of the AMS, David H. Bailey, Jonathan M. Borwein, Marcos López de Prado, and Qiji Jim Zhu, "make the case that the vast majority of claims being made for quantitative investment strategies are false," and "by calling it fraud, the academics command attention, and investors would be wise to beware." The Notices authors alert us that there are investment managers and advisors who don't use rigorous mathematics and "by tweaking the strategy until it neatly fits the historical data" those managers are "deliberately or negligently, misleading clients." But as Foley points out, the authors are positive about improving modeling and limiting risks. Marco Lopez de Prado offers open source software (quantresearch.info) and Bailey "suggests that a regulatory body such as Finra could step in to promote best practice in the marketing of mathematical claims."
Bloomberg's Kishan sums up the problems as 1) "Strategies that use computer models to predict future market moves are often based on selective historical data" and 2) according to the authors, "mathematicians in the 21st century have remained disappointingly silent with the regards to those in the investment community who, knowingly or not, misuse mathematical techniques such as probability theory, statistics and stochastic calculus. Our silence is consent, making us accomplices in these abuses."
See: "Ban pseudo-mathematics from investing," by Stephen Foley, Financial Times, April 16, 2014 (requires a subscription) and "Computer Models Often Use Unsound Math, Researchers Say," by Saijel Kishan, Bloomberg News, April 11, 2014. Also see the financial-math blog by de Prado and Bailey.
--- Annette Emerson
It's not that I didn't like Freeman Dyson before -- to tell the truth, I barely knew the guy -- but what's certain is that I like him a whole lot more having read Thomas Lin's recent interview on the occasion of his 90th birthday. Dyson is the quintessential mathematician's mathematician -- a skeptic, a humanist, an iconoclast, a hater of faculty meetings and a problem solver without pretensions of grandeur -- and his musings on science and his ongoing and rich career are full of charm and wisdom. Like many people of a certain age, Dyson was attracted to mathematics by E.T. Bell's tragically gendered classic "Men of Mathematics," whose pull, says Dyson, was in the way it "showed the mathematicians as being mostly crooks ... and not very clever ... it told a kid that 'if they can do it, why can’t you?'" So inspired, Dyson pursued mathematics and science partly as "a subversive activity," and partly as an exercise in creative self-expression. "I had this skill with mathematical tools, and I played these tools as well as I could just because it was beautiful," he says. "I'm not a person for big questions. I look for puzzles. ... I don't care whether they’re important or not." Nonetheless, his quest for interesting puzzles and his singular genius led him Dyson to make influential and often seminal contributions to a huge variety of disciplines -- including number theory, quantum field theory, random matrix theory, medical research (by helping to develop the low-power nuclear reactors that produce isotopes for research hospitals), and, as recently as 2012, evolutionary game theory. But Dyson remains thoroughly humble. "That's really my skill, just doing calculations and applying mathematics to all kinds of problems," he says. "Mathematics applies to all kinds of things. That's one of the joys of being a mathematician." Indeed. A similar humility comes through in Dyson's reminiscences about his groundbreaking work alongside Richard Feynman on quantum electrodynamics, which are worth viewing the accompanying mini documentary to hear.
Dyson's deep concern for social issues led him to a second career as a public intellectual, writing regularly for The New York Review of Books and penning a number of titles for popular audiences. He's fought for peace while advising the military on logistics to help them avoid unnecessary casualties, and he's been in the news recently for his controversial views on climate change. "What I'm convinced of is that we don't understand climate," he says here. "I'm not saying the majority is necessarily wrong. I'm saying that they don't understand what they're seeing." An article in the New York Times Magazine on Dyson and the climate change controversy surrounding him exposes the nuances of both Dyson's personality and his climate change skepticism. Not only does Dyson question the damage that carbon dioxide does to the planet's ecosystems, he believes coal is indispensable in fueling the "the move of the populations of China and India from poverty to middle-class prosperity," which "should be the great historic achievement of the century ... To me that's very precious." Dyson's views on the Ph.D., which are similarly controversial, and have similarly humane and sensible motivations, will resonate with many academics. "I'm very proud of not having a Ph.D.... It forces people to waste years and years of their lives sort of pretending to do research for which they're not at all well-suited," he says. "The Ph.D. takes far too long and discourages women from becoming scientists, which I consider a great tragedy. So I have opposed it all my life without any success at all." You win some, you lose some. Happy birthday, Mr. Dyson. (Photo: Freeman Dyson, Professor Emeritus, Institute for Advanced Study.)
See: "At 90, Freeman Dyson Ponders His Next Challenge," by Thomas Lin. Quanta Magazine, 31 March 2014.
--- Ben Polletta
Should you take dating advice from a mathematician? According to a recent post on the Binghamton University blog bupipdream: If that mathematician is Hannah Fry (pictured above), then yes. A lecturer at the Centre for Spacial Analysis at University College London--and self-proclaimed "all round bad-ass"--Fry applied her research in fluid dynamics and complexity theory to tease out some of the less amorous aspects of love in a TEDx talk at Binghamton earlier this week.
In the talk she shares her top three tips for finding love: don't be afraid to look a little bit ugly, know when to settle, and if you find yourself in a relationship, speak out about what bothers you.
Fry supports these bits of wisdom with calculations and mathematical reasoning. On having perhaps a less-than-perfect visage, Fry says, “it’s [the] spread that counts…If some people think you’re attractive, you’re actually better off having some people think you’re a massive minger."
A finding supported by the analysis of the nerd-friendly number-crunching dating site OkCupid.
On knowing when to partner-off and settle down, Fry employed a technique called optimal stopping theory. "In the wild there are certain types of fish who follow this exact structure," Fry says, “they reject all the fish that come up to them during the first 30 percent of the mating season. Then…they accept the next fish that is bigger and burlier than those that had come before.”
Such advice is mathematically sound for humans too, Fry argues, especially when we consider that a suitable mate is almost as hard to find as a highly evolved civilization somewhere in the Milky Way.
For more mathematical lifehacks, perhaps less romantic in nature, follow Hannah Fry on Twitter @FryRSquared. (Photo courtesy of Hannah Fry.)
See the article: "TEDx: 'The Mathematics of Love'," by Nicolas Vega. Binghamton University Pipe Dream, 31 March 2014.
This article discusses the unusual career of Matt Parker, described as a "stand-up mathematician"--he does stand-up comedy based on mathematical themes. With a degree in applied mathematics earned in his native country of Australia, Parker moved to England and taught school mathematics before realizing that his true calling was stand-up comedy. Although his comedy skits play on people's school memories of Venn diagrams and algebra, he's not aiming merely to poke fun at mathematics. "I am not just making jokes about maths because I think it is an easy way to do comedy," he told New Scientist. "I honestly want to make people enjoy maths more and realise there is more to maths than what they learned at school." The article highlights Parker's 4-dimensional cube crash video on YouTube as an example of his comedy.
See the article: "Dream Job: Stand-up mathematician," by Jessica Hamzelou. New Scientist, 27 March 2014.
The first two articles cited below discuss the use of mathematics to locate airplane wreckage. The BBC story discusses the June 2009 Air France flight that went missing while flying from Rio de Janeiro, Brazil, to Paris, France. France's aviation accident investigation authority contacted the American firm Metron Inc, to get help. The Metron statisticians used Bayesian techniques (named after the 18th century mathematician Thomas Bayes who created them) to optimize the search for the aircraft wreckage. A first crack at locating the plane did not pan out, but a few months later the Metron team adpated their model and successfully guided searchers to the right spot. The CNN story says that a British company, Inmarsat, and the UK's Air Accidents Investigation Branch collaborated to produce a novel mathematical process for analyzing information about the most likely flight path of the Malaysian Airlines plane that has been missing since March 8. Calling the process "groundbreaking," an Inmarsat official told CNN that the new calculations "underwent a peer review process with space agency experts and contributions by Boeing."
See the articles "How 'groundbreaking' number crunching found path of Flight 370," by Thom Patterson. CNN, 25 March 2014, and "MH370 Malaysia plane: How maths helped find an earlier crash." BBC News Magazine, 22 March 2014. Other coverage: University of Texas at Dallas prof John Zweck explains to NBC News how great circles and trig could help locate the jet and more on Bayes' Theorem in this NPR segment.
Dana Mackenzie is a math and science writer, and author of the recent The Universe in Zero Words: The Story of Mathematics as Told Through Equations, as well as the three most recent volumes of the AMS series What's Happening in the Mathematical Sciences. Mackenzie's parents inspired him in both writing and math: His mother taught him to read and write and typed and bound his stories, while his father taught him the beauty of equations. Mackenzie got his PhD at Princeton and taught at Duke and Kenyon before becoming a science writer. He has many interests that are mentioned in the profile, including chess, hula, and animals. At the end of the article, Mackenzie tells the author of the article a story of the time he hosted a reading for his book The Big Splat: "He [Mackenzie] invited the Santa Cruz Astronomy Club, which set up telescopes outside. A nearby drugstore thought it was a bomb, so the police came, looked through the telescopes and left." Mackenzie concludes the story with "There's something amusing to me about calling the police to save ourselves from science." (Photo: Courtesy of Dana Mackenzie.)
Read the article "Dana Mackenzie, Santa Cruz County Stories: Chess champion balances science writing, hula dancing," by Bonnie Horgos. Santa Cruz Sentinel, 23 March 2014.
--- Mike Breen
Time profiles statistician Nate Silver, who runs FiveThirtyEight, the "data-crunching digital publication" that predicts, among other things, political and sports results. Dickey writes that Silver "evangelizes on behalf of data and statistics in a profession where they have historically had little place and then frets about the overuse of numbers." He started out at Baseball Prospectus, where he forecast players' seasons and played online poker. From there, he blogged about politics, and moved to New York City, where "one of his most memorable projects, a ranking of New York City's top 50 neighborhoods," was published in New York magazine. Silver became more well-known after he rightly predicted Obama's victory in 2012. FiveThirtyEight was hosted by the New York Times from 2010-2013, but Silver was restless to "bring a generation of data journalists under his tent" in all forms of media, and FiveThirtyEight migrated to ESPN. The photograph of Silver in the article shows in the background some of the many topics that are the subjects of his analysis: midterm elections, tournament brackets, long-term unemployment, Venezuela oil, climate change, minimum wage, taxis and weather extremes. The article focuses on some of the talent that ESPN has "poached" from the Times, The Wall Street Journal and other places.
See the article: "Hey Sports Fans, It's Time for Math Class," by Jack Dickey. Time, 17 March 2014. [Editor's note: Carl Bialik, previously "The Numbers Guy" at The Wall Street Journal, and Joint Policy Board for Mathematics' 2008 Communications Award recipient, is now at FiveThirtyEight, and shows "How Nate Silver Hires," a chart Silver developed of qualities he seeks in potential candidates.]
--- Annette Emerson
Pi Day has passed, but Ruth Charney’s thoughts on what parents and teachers can do to get girls to excel and pursue mathematics ring true year-round. Charney, president of the Association for Women in Mathematics (AWM), says that she’d like to see more women in mathematics, and a day when words used are "Woman" + "Mathematician" = "Mathematician" and not "Woman mathematician." She says, "I think the way to go when talking to children is to show that math is really about puzzle solving, not just doing some rote equations," and goes on to recommend some ways to engage girls in mathematics for the long-run. She suggests girls join a Math Circle, go to a summer math camp, watch Numberphile and TED ED videos, visit Cut the Knot website, and find a mentor.
See the article: "Calculating women: How to get more girls into math," by Lisa Suhay, Christian Science Monitor, 14 March 2014.
--- Annette Emerson
Media covered a recent study published in the Proceedings from the National Academy of Sciences ("How stereotypes impair women's careers in science") showing that both men and women believe that men are better at math—even though in fact women do as well in math as men. One factor is that in general women tend to discount their own (and other women's) ability. In one experiment female and male job "applicants" (subjects in this experiment) tested equally well in arithmetic but employers (male and female) were more likely to hire the male, based on both gender stereotyping and how confident the men were about their arithmetic test results as opposed to the women.
Actress/mathematician Danica McKellar, committed to addressing the problem of female insecurities about their abilities in math, has written several books for pre-teen and teen females--to entice them into learning math, reduce their fears, and teach them some math concepts. She says in an interview with Learning first Alliance that "on top of the stereotypes about how difficult and "nerdy" it is to study math, girls are also getting the message that they're not supposed to be good at it," and tells girls that they can do math, that it is cool to be smart, and that the confidence they have by knowing math will make them more confident in future work and life experiences.
In "Debunking Myths about Gender and Mathematics Performance" (Notices of the AMS, January 2012) Jonathan M. Kane and Janet E. Mertz say "boys and girls may be born similar in their innate intellectual potential but end up displaying differences due to a variety of sociocultural factors present in their environment." The piece focuses on school performance, but of course early education and test results impact higher education and career choices. The authors cite Gender Gap in Math Performance vs. Equity Indexes in countries around the world, and one of their conclusions is: "Eliminating gender discrimination in pay and employment opportunities could be part of a win-win formula for producing an adequate supply of future workers with high-level competence in mathematics. Wealthy countries that fail to provide gender equity in employment are at risk of producing too few citizens of either gender with the skills necessary to compete successfully in a knowledge-based economy driven by science and technology." It would seem that early intervention to cultivate self-confidence in girls who study and like mathematics is an important step in changing perceptions--and job prospects--of females.
The Women Doing Mathematics poster shown above highlights women mathematicians working in various fields.
See: "Study: Women Who Can Do Math Still Don't Get Hired," by Shaila Dewan, New York Times, 11 March 2014 and "Can women do math? New study finds both sexes believe men are better - regardless of a person's actual ability," by Mark Prigg. Daily Mail, 11 March 2014.
--- Annette Emerson
The beautiful, and for some, terrifying symmetry of the Chair-O-Plane means that understanding the movement of one rider is enough to understand the movement of every rider. Image: Flickr Creative Commons, Eric.Parker .
As reported in news@Northeastern, finding and exploiting the symmetries in complicated mathematical systems is the bread and butter of Northeastern University's Ivan Loseu (below), winner of a 2014 Sloan Research Fellowship.
Ivan Loseu, originally from Belarus, will spend his next two years as a Sloan Research Fellow working on his research in representation theory. Image: Courtesy of Michael Finkelberg.
Math Digest reached Loseu by Skype to ask him about symmetries, and his current research in representation theory. As complex math is often best understood through motivating examples, he points us towards Hamiltonian mechanics.
"Let's say that we have a mechanical system with symmetry," he says. "This symmetry gives rise to conservation laws, and using conservation laws you can reduce the dimension, or the number of variables involved."
But what does a highly symmetric Hamiltonian system actually look like?
"Well…," Loseu looks around on his desk as though to avail himself of the nearest Hamiltonian system, "take this!" He removes one of his headphones and holding the cord in his hand, begins spinning the earbud, "as you rotate this headphone the laws of motion don't change."
"Since you have additional constraints on how this object can move," he explains, you can really think about the whole headphone system as having one less dimension. This process is called reduction. But because of the symmetry, it's also possible to reclaim the original system from the reduced system, something which can often be quite difficult in mathematics.
Of course mankind's fascination with the beautify and structure of symmetry is nothing new. In a TED Talk (embedded below), University of Oxford professor Marcus du Sautoy, explains how sophisticated mathematical concepts are embedded in ancient paintings:
For other ways that symmetries can make you rich and famous--or at least rich--check out this Freakanomics Radio podcast.
Congratulations to all of the 2014 Sloan Research Fellows, we wish you many years of success and symmetry.
See the article: "Magic and symmetry in mathematics," by Angela Herring. news@Northeastern, 11 March 2014.
--- Anna Haensch
It's a little hard to believe that a word like bracketology (the process of predicting the games in the NCAA Basketball Tournament), which didn't even exist until a few years ago, is now used commonly, but because of the popularity of the tournament, often billed as March Madness, it's used--and performed--frequently. Tim Chartier (left) of Davidson College and Math Ambassador for the MAA, has been quite busy recently doing interviews because of his successful use of math to predict the outcomes of games in the tournament. Chartier and Davidson students have been looking into predicting outcomes of the NCAA Men's Division I College Basketball Tournament for a few years and now that Warren Buffett has offered $1 billion to anyone who can predict every game in the tournament correctly, linear algebra has acquired some added luster. In Chartier's class's first year of using math to make picks, one Davidson student, Daniel Martin, finished in the top 1% of predictions in ESPN's online contest. That won't get you Buffett's billion (in fact, looks like we'll all have to wait until at least 2015), but it could be enough to win your office pool. In this front-page article, Chartier explains how he and his students use math--and some intution--to make picks in the tournament. Weights are assigned to various factors, such as the quality of a team's opponents--which turns out to be very important--to arrive at predictions. This year, Chartier is trying to incorporate momentum into the algorithm: "Yes, you have momentum down the stretch, but are you doing that against good teams? You’ve been able to sustain winning streaks, but are you doing that against good teams?" Photo: Laura McHugh, MAA.
Read the article: "Math whiz unlocks NCAA bracket formula," by David K. Li. New York Post, 10 March 2014. Chartier's work to help predict outcomes in the tournament was covered by many in the media, including The Atlantic, The New York Times, Bloomberg TV, and the CBS Evening News.
--- Mike Breen
A Japanese researcher's "rules of thumb" for scientists designing the location of physical infrastructure for internet connectivity may help ensure that future disasters, such as earthquakes, don’t intersect and damage connections between network nodes. The researcher, Hitoshi Saito, developed the rules using the principles of integral geometry, under the assumptions that a disaster would occur within a finite area, and that nodes inside this area would fail with a certain probability. He then proved the validity of these rules by testing various network configurations against data from major earthquakes Japan has experienced. If implemented, his rules would represent a change from network design focused on protection from disaster to design aimed at avoiding disaster altogether through strategic node placement and interconnection. The research is posted on the ArXiv.
See the article: "Mathematical Proof Reveals How To Make The Internet More Earthquake-Proof." MIT Technology Review, 3 March 2014.
--- Lisa DeKeukeleare
This obituary describes the life of mathematician and civil rights activist Lee Lorch. The article puts particular emphasis on Lorch's leadership in the campaign to desegregate Stuyvesant Town in Manhattan, an effort that helped make housing discrimination illegal nationwide. After this campaign, Lorch was fired from his job at City College, despite an excellent record as a scholar and teacher (years later, in 1990, City College awarded him an honorary doctorate). Positions at Penn State and Fisk University likewise foundered due to his reputation as a "troublemaker." Lorch finally got a position at Philander Smith College, an all-black institution in Little Rock, Arkansas. There he and his wife were among those assisting a group of African American schoolchildren who attended a white school. This group, known as the "Little Rock Nine," became emblematic of the civil rights struggle. Around this time Lorch was called before the House Un-American Activities Committee, where he refused to answer questions about his supposed ties to Communists. Philander Smith College did not renew his contract, and Lorch was blacklisted from U.S. colleges and universities. In 1959, he and his family moved to Canada, where he first joined the faculty at the University of Alberta. He went to York University in Toronto in 1968 and remained there for the rest of his career.
Born in New York City in 1915, Lorch received his PhD in 1941 from the University of Cincinnati and has 85 publications in MathSciNet. Active in the AMS, Lorch often brought before the Council cases concerning human rights and discrimination. When he received the Gung and Hu Award for Distinguished Service from the MAA in 2007, the crowd at the prize ceremony gave him a long standing ovation. The ceremony took place at the Joint Mathematics Meetings in New Orleans a year and a half after the devastation of Hurricane Katrina, and Lorch used his acceptance speech to remind the audience to reach out to their mathematical colleagues in the New Orleans area. Known for his humanity, warmth, and humor, Lorch served as a conscience for the mathematical community and will be greatly missed.
See the article: "Lee Lorch, Desegregation Activist Who Led Stuyvesant Town Effort, Dies at 98," by David Margolick. The New York Times, 2 March 2014. [Also see "Mathematician Lee Lorch fought tirelessly against racism," in the Toronto Star.]
--- Allyn Jackson
Edward Frenkel, who has been frequently covered by the media recently, wrote this Op-Ed for the Los Angeles Times in which he compares current math education with teaching art by teaching only whitewashing and never allowing students to see masterpieces. He acknowledges that the math taught now to almost everyone is important but thinks that students should be offered glimpses of modern mathematics by being exposed to subjects such as symmetry groups, modular arithmetic, and Riemannian geometry. Those subjects can't be mastered by young students but Frenkel writes of his visit with 5th and 6th graders in New York:
I used a Rubik's Cube to explain symmetry groups: Every rotation of the cube is a "symmetry," and these combine into what mathematicians call a group. I saw students' eyes light up when they realized that when they were solving the puzzle, they were simply discerning the structure of this group.
Abstraction is an important skill in today's world, and math can help people acquire that skill. Frenkel thinks that allotting about 20% of class time to the "power and exquisite harmony" of modern mathematics would break the vicious circle of people who hate math and aren't good at it, as well as doing away with the question "Why study math?"
See the article: "How our 1,000-year-old math curriculum cheats America's kids," by Edward Frenkel. Los Angeles Times, 2 March 2014. [Also see "5-Year-Olds Can Learn Calculus," by Luba Vangelova in The Atlantic. In this article, Vangelova writes about educators who are letting children experiment with simple aspects of complex subjects (such as using mirrors to introduce transformations), as opposed to teaching complex parts of simple subjects (e.g. multiplication table drills).]
--- Mike Breen
In January 2009, University of Cambridge mathematician Timothy Gowers posted a theorem on his blog and invited readers to work together to prove it. To his surprise, after 2 months--and almost 1,000 comments later--he could declare the theorem proven. Gowers published the proof under the pseudonym "Polymath," and so began the now 5-year-old crowd-sourcing mathematics project of the same name (screen shot at left). The Polymath project "has a dedicated website where people can post and debate suggestions for new challenges--and, if they agree that the challenge is worthwhile, circulate ideas for its solution." Projects that are "broadly accessible and of interest to a large number of mathematicians" have had the most success, notes UCLA mathematician Terence Tao. For example, one month after Yitang Zhang's breakthrough work on 'near-twin' primes became public last May, Tao began coordinating a Polymath project--dubbed "Polymath 8"--to see if the limit between pairs of primes couldn't be reduced. By November, that limit had been reduced from 70 million to 600. Without the kind of rapid, collaborative approach made possible by Polymath, Tao speculates that this result would have taken years.
See the article: "Crowd-sourcing: Strength in numbers," by Philip Ball. Nature, 27 February 2014, pages 422-423.
--- Claudia Clark
In this piece, George Dvorsky gets tips on making sense of "stupid large" numbers from mathematician Spencer Greenberg, a hedge fund manager and blogger who studied machine learning at New York University and writes for AskAMathematician.com. More germanely, Greenberg is the founder of ClearerThinking.org, an organization or possibly website dedicated to helping individuals overcome their cognitive biases. One of these biases, Greenberg suggests, is an inability to think coherently about very large numbers. While people seem to have an innate capacity to reason about small numbers, the kinds of numbers used to quantify phenomena on the scale of countries, planets, and galaxies lie well outside the dynamic range of this number sense. As a result, numbers like a quadrillion and a trillion can seem equivalently huge, despite the fact that a quadrillion is a thousand times larger than a trillion. Greenberg's suggestions on handling this kind of numerical overload mostly boil down to unit changes--expressing the U.S. debt as debt per capita, for example, or as a percentage of the U.S. annual GDP. Some of these conversions are quite creative, however--for example, thinking of 400,000 people as "20 hockey arenas worth," or converting the risk of death from hang gliding from a proportion of hang gliders (1 in 116,000) to a proportion of the baseline risk of death (for a 30-year old, a day that includes hang gliding is 3.2 times likelier to be fatal than a day that doesn't). Another neat trick is to introduce time to understand numbers like San Francisco's population of 4.3 million: if you spoke to every resident of San Francisco for one minute, and did that for eight hours a day (sans lunch break), it would still take you 24 and a half years to "meet" them all.
Greenberg warns against choosing irrelevant units--such as converting monetary sums to heights in stacked pennies--and against using units that are themselves hard to comprehend, such as tons. But he admits that no matter how you slice them, some numbers--such as the number of stars in the Milky Way (300 billion, or roughly 42 stars for each of Earth's 7.1 billion human inhabitants)--remain deafeningly large. "When dealing with large numbers," he says, "we often just have to 'do the math'."
Read the article: "How to Comprehend Incomprehensibly Large Numbers," by George Dvorsky. Io9, 26 February 2014. [Coincidentally, the AMS is publishing a book on big numbers, Really Big Numbers, which is its first children's book.]
--- Ben Polletta
Perhaps not surprisingly, President Obama's BRAIN Initiative is exactly as involved as President Obama's brain, itself. Its "overarching goal," says Stanford neuroscientist William Newsome--co-chair of the National Institutes of Health panel establishing the Initiative's priorities--is "to map the circuits of the brain, measure the fluctuating patterns of electrical and chemical activity flowing within those circuits and to understand how their interplay creates our unique cognitive and behavioral capabilities." The new science of connectomics--the application of the mathematical and physical theory of networks to the brain's multifaceted architecture--is concerned with the first of these daunting goals. Connectomics attempts to understand the brain as a graph--a collection of nodes connected by edges--and to relate the unique properties of this graph to the functioning of the brain. While this mirrors the physical reality of the brain--which is a collection of cells (neurons) electrically and chemically interconnected to one another (through synapses)--mapping the underlying graph of the human brain at the single-neuron level is a long way off. Instead, researchers study exact maps of the brains of simpler organisms--such as the roundworm C. elegans, which has 383 neurons instead of the ~85 billion of the human brain--and construct relatively coarse maps of the human brain's connectivity. In these finest of these coarse maps, being constructed by the NIH's Human Connectome Project, the nodes are parcels of "gray matter" (neuron-containing tissue) a cubic millimeter in size. The edges in such maps may reflect anatomical connectivity data obtained from imaging the "white matter" tracts (rivers of neuronal processes that terminate in synapses) that join these parcels, or functional connectivity data obtained by observing which parcels exhibit correlated dynamics.
Already, interesting conclusions about the brain's network architecture have emerged from these partial connectomes. For example, both the C. elegans brain and human functional and anatomical connectomes are characterized by a small world architecture--meaning that they exhibit a few highly connected nodes or "hubs," and many sparsely connected nodes. In the human brain, these hubs are found in non-overlapping sub-networks related to important brain functions, such as vision, movement, hearing and touch. And while these functional sub-networks don't overlap much, it turns out that the hubs associated with them are highly connected to each other, forming a so-called "rich club" which may serve to integrate multiple streams of information into a coherent whole. Furthermore, cognitive dysfunction, such as that seen in schizophrenia, attention deficit disorder, and autism, is accompanied by dysfunction at the network level: while schizophrenics exhibit more variable connectivity than normal, subjects with ADD exhibit weaker connectivity, and autistic subjects have more highly linked brains. So although we may be a long way from a final count of the BRAIN Initiative's accomplishments, the exit polls from connectomics look very promising.
See the article: "Cataloging the connections," by Tom Siegfried. Science News, 22 February 2014, pages 22-26.[Learn more about math and the brain in this Mathematical Moments podcast with Van Weeden.] Image: L.L.Wald and V.J.Wedeen, Martinos Center for Biomedical Imaging and the Human Connectome Project.
--- Ben Polletta
Although scientists across a range of disciplines commonly use a statistic known as a p-value to evaluate the significance of observations in a data set, some researchers argue that the p-value is often misapplied and misinterpreted. The p-value for an observed correlation between two variables, for example, is the probability of obtaining such observations if no such correlation exists, and scientists often consider a correlation significant--and worthy of publication--if this probability is less than 0.05. The problem is, the p-value alone does not account for the probability that such a correlation exists, and results with significant p-values often are not reproducible because a low probability for the existence of a correlation can lead to a high rate of false positives. Another problem is "p-hacking," the engineering of data collection and analysis to obtain a significant p-value. Some researchers propose that applying multiple statistical techniques to evaluate the validity of results would help mitigate some of the problem associated with p-values, but moving away from such a widely popular statistic as the p-value probably will require a cultural shift in statistical instruction, analysis, and presentation.
See the article: "Statistical Errors," by Regina Nuzzo. Nature, 13 February 2014, pages 150-152.
--- Lisa DeKeukeleare
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