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Cool Jobs: Data Detectives | Science News for Students 8/31/17, 10�15 PM Cool Jobs: Data detectives | Science News for Students 8/31/17, 1015 PM MATHEMATICS HEALTH MATERIALS SCIENCE Cool Jobs: Data detectives From health and the environment to sports, statisticians uncover valuable information that would otherwise remain buried in mountains of data BY DANA MACKENZIE DEC 17, 2013 — 9:30 AM EST Yoenis Cespedes (shown here) led the Oakland Athletics to the Major League Baseball playoffs in 2012. Before the season’s start, the Athletics signed Cespedes to a large contract, even though he had never played an inning of baseball in the United States. What’s more, other teams considered him too big a risk. But Farhan Zaidi, a statistical guru, based his decision “on the numbers.” Michael Zagaris, Oakland Athletics This is one in a series on careers in science, technology, engineering and mathematics made possible by support from the Northrop Grumman Foundation. When Lee-Ann Hayek got her first job at the Smithsonian Institution in Washington, D.C., she wasn’t expecting to spend her whole career there. She had just received her doctorate in statistics. She recalls thinking it would be fun to work at one of the Smithsonian’s famous museums or https://www.sciencenewsforstudents.org/article/cool-jobs-data-detectives Page 1 of 11 Cool Jobs: Data detectives | Science News for Students 8/31/17, 1015 PM research centers. So, “I just wrote them a letter and said, ‘I’ll dust your elephants if you want!’” Today, 35 years later, Hayek works at the National Museum of Natural History. As the Smithsonian’s chief mathematical statistician, Hayek doesn’t do any dusting. (She does, however, get to see its stuffed elephant, Henry, any time she wants.) A detective of sorts, Hayek digs into the raw numbers, called data, churned up by hundreds of Smithsonian experts doing cutting-edge research in a wide range of fields. Statisticians like Hayek specialize in identifying patterns in data. Some work to make the data more manageable. Others may use it to make predictions. Just as importantly, their work provides a reality check for other scientists. Statisticians diagnose patterns that may appear to be there but are probably due to what is called “noise” — unwanted and random variations in data. The scientists Hayek works with may be the world’s leading experts on a particular topic. Still, those experts may not understand the best way to analyze the data they collect. “Theory is well behaved, but data never are,” Hayek jokes. The role of a statistician is often misunderstood. A lot of people think that statisticians just collect mountains of numbers. But their real job is to transform data that others have collected into useful information. For example, laboratory tests on the blood of wild pandas generate data. Statisticians can use those data to answer questions. One might be whether the vaccines used on pandas truly work to prevent disease. Veterinarians can then use that information to improve panda care. Here we meet three statisticians who have made a career of sifting through numbers to answer hard questions. The trends they discover bring meaning to Lee-Ann Hayek shown within the diverse aspects of our world, from art and animals to Smithsonian Institution's paleobiology brains and baseball. collection, which contains more than 40 million fossils. Such collections “I can solve that!” generate scientific questions and Though not part of the Smithsonian Institution, the hypotheses. They also provide National Gallery of Art mountains of raw data. Hayek's job is (http://www.nga.gov/content/ngaweb/about.html) is to turn those data into information — one of many museums clustered along a stretch of and answers. parkland in Washington, D.C., known as the Mall. The Jennifer Jett National Gallery has one of the world’s largest collections of portrait medals from the Italian Renaissance. That’s an artistic period that ran from about 1350 to 1600. One day, the National Gallery’s senior chemist, Lisha Glinsman, came to Hayek with a question. Could the different recipes used to make bronze help experts figure out which artist had created any particular unsigned medal? What an interesting question, Hayek thought. So she decided to look for an answer. https://www.sciencenewsforstudents.org/article/cool-jobs-data-detectives Page 2 of 11 Cool Jobs: Data detectives | Science News for Students 8/31/17, 1015 PM Statisticians learn to analyze data in several ways. The simplest is through descriptive statistics. Here they take a collection of data and describe it mathematically. For instance, statisticians may measure its mean (or average value) and the variance (a measure of whether the data are all close to the mean or spread far apart). Using descriptive statistics, Hayek found each bronze medal had been made from one of seven or eight different alloys (or mixtures of different metals). Each alloy, for example, contained different average percentages of copper, tin, lead or zinc. The biggest surprise: No alloy was the exclusive recipe of just one artist. In the same way that a sculptor might select from among several types of stone, depending on what subject he was portraying, each bronze-worker used several alloys. A portrait medal of Giovanna degli This discovery “just turned the project around,” Hayek Albizzi, created by artist Niccolò says. It showed that bronze in Renaissance Italy had Fiorentino in Florence, Italy, around not been a single generic product, prepared by each 1486. Statistical analysis revealed workshop in its own way. Instead, there were many Renaissance artists such as Fiorentino types of bronzes. Craftsmen chose different recipes for used a variety of bronze alloys in different purposes. And it seemed no accident, Hayek creating popular portrait medals. says: “These people knew what they were doing!” Courtesy National Gallery of Art, Panda stats Washington A second type of statistics is called inferential. It typically involves “significance tests.” These math tests try to determine whether an apparent pattern is real or likely due just to chance. A project Hayek worked on involving giant pandas offers a good example. For many years, scientists in China had been vaccinating their native pandas against diseases common in dogs and other domestic animals. In fact, the experts used vaccines that had been designed for dogs. Some Chinese veterinarians worried that dog vaccines might not protect pandas all that well. To check that out, the veterinarians sent Hayek data on blood samples. The vets had collected the blood from 19 pandas in China over a six-year period. At once, Hayek detected a troubling pattern. https://www.sciencenewsforstudents.org/article/cool-jobs-data-detectives Page 3 of 11 Cool Jobs: Data detectives | Science News for Students 8/31/17, 1015 PM The body produces antibodies as part of its immune response. Antibodies neutralize, tag or destroy viruses and other foreign substances in the blood. A vaccination should leave a panda’s antibody levels high. That would give these bears immunity to a virus, lowering their risk of infection. Vaccines also should be consistent, producing similar results every year. But Hayek found that panda antibody levels changed dramatically from year to year. Something must be wrong! It wasn’t clear right away if the variations were real and the vaccine’s fault. Random fluctuations in the pandas’ In October 2013, an eight-week-old blood might cause antibody levels to spike one year and panda cub at the Smithsonian fall the next. If the vaccine wasn’t to blame, the Institution’s National Zoo visited the scientists might spend a lot of money trying to fix a veterinarian to get its first vaccine. A problem that didn’t exist. statistical study by Lee-Ann Hayek analyzed the effectiveness of vaccines But Hayek’s mathematical tests left little doubt. She detected variations in immunity that were too big and on China’s wild pandas. too systematic to be due solely to chance. Her work Abby Wood, Smithsonian’s National Zoo confirmed what her veterinarian colleagues had suspected: China’s vaccine makers were not producing a consistent product. In some years, vaccine quality was poor. Pandas in those years lacked good protection from disease. This shows why statistics is like detective work. Descriptive statistics detect a pattern that’s out of the ordinary. Inferential statistics catch the culprit (or prevent the arrest of an innocent bystander). “It doesn’t always take advanced math,” Hayek explains. “But it does take a tremendous amount of reading and knowledge to look at a problem and say, ‘I can solve that. I don’t know how, but I know that I can.’” Statistics on the brain You might say that Brian Caffo has numbers on the brain. A whole lot of them. Caffo’s specialty is a kind of brain scan called “functional magnetic resonance imaging” — or fMRI for short. Unlike X-rays, which show only the brain’s structure, the colorful pictures created using fMRI show the brain at work. Neuroscientists are especially interested in seeing which parts of the brain light up (and which don’t) when someone does a particular task. This helps them map connections between different parts of the brain. https://www.sciencenewsforstudents.org/article/cool-jobs-data-detectives Page 4 of 11 Cool Jobs: Data detectives | Science News for Students 8/31/17, 1015 PM But scans of active parts of the brain don’t start out as colorful maps. They begin gray, fuzzy and sometimes full of holes — like Swiss cheese. At this early stage, even a neuroscientist may not be able to distinguish between truly active and inactive areas. It’s Caffo’s job to sharpen those fMRI images into pictures that doctors can understand.
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