Each year, consumers create 16.3 zettabytes of information—enough to fill over 127 billion iPhones. Sorting through all this information is like trying to find a needle in a haystack the size of California.
Within these treasure troves of data are valuable insights waiting to be discovered. Data scientists use statistics, math, and information technology to sort through enormous datasets with millions of variables, looking for patterns. Yet combing through this information takes immense power, not to mention computer memory. So do they sort through it all?
That’s where people like Zhigen Zhao, associate professor of Statistical Science at the Fox School, come in.
Zhao and his statistician colleagues invent new ways to use statistics, overcome computation limitations, and see patterns through the noise. Their discoveries range from a newly patented methodology that enables users to analyze millions of data points in seconds to a new threshold for pinpointing statistical significance.
Deciphering Genetic Codes
Humans have 20,000 genes in our DNA. Much like data, decoding how each gene interacts with another can provide valuable insight, in this case into a person’s health. With over 190 million possible pairs, that’s a lot of variables to test.
“Years ago, 10,000 was considered a big data set, but not anymore,” says Zhao. When using standard algorithms like distance correlation, statisticians run into issues with computation speed, and the old algorithms can’t keep up with the large datasets available today.
Zhao and his colleagues devised a methodology that can analyze all of these variables in seconds. “Our method only takes two-tenths of a second to finish this kind of calculation,” says Zhao. His computer would crash when using older algorithm to analyze a dataset of that size.
“People’s health can depend on a specific combination of their genes,” says Zhao. This revolutionary methodology, which was recently approved for a patent, can identify certain combinations of genes that may help doctors understand medical issues ranging from heart disease and Alzheimer’s to obesity and alcoholism.
Discovering Differences in Education
With millions of pieces of information, statisticians and data scientists often grapple with the problem of false discoveries—inferring a pattern that is not truly significant. Statisticians try to account for these false discoveries, but this may lead to a less complete picture of the data.
Zhao and his colleagues created a new algorithm to reduce the number of false discoveries while keeping more pertinent patterns than other methods. Zhao’s team applied this algorithm to school districts in California, analyzing standardized test scores of students from over 4,000 elementary schools.
The researchers compared pass rates from two groups of students, the socioeconomically advantaged and the socioeconomically disadvantaged. Normally, the advantaged students will have higher scores than their disadvantaged counterparts. However, Zhao used his algorithm to identify schools that have unusually small or unusually large differences between the two populations—where the disadvantaged students were either significantly underperforming or overperforming in statewide math tests.
Their new algorithm found more schools whose populations have significant differences in test scores, providing a more complete understanding of the dataset. “The main idea for this method is to incorporate school district information to get a new threshold,” says Zhao. “The standard method, which doesn’t include this information, can be either overly conservative or overly liberal.” This kind of refined analysis can help district and state policymakers to reallocate resources to support underperforming schools or to imitate overperforming schools.
From education to healthcare and everything in between, Zhao and his fellow statisticians sort through enormous datasets, finding new ways to compute that better our everyday lives.
This story was originally published in On the Verge, the Fox School’s flagship research magazine. For more stories, visit www.fox.temple.edu/ontheverge.
Peace has finally been brokered in a long-standing argument between two schools of thought in statistical science.
Research from Deep Mukhopadhyay, professor of statistical science, and Douglas Fletcher, a PhD student, was accepted for publication in Scientific Reports, a journal by Nature Research. Their research marks a significant step towards bridging the “gap” between two different schools of thought in statistical data modeling that has plagued statisticians for over 250 years.
“There are two branches of statistics: Bayesian and Frequentist,” says Mukhopadhyay. “There is a deep-seeded division, conceptually and operationally, between them.” The fundamental difference is the way they process and analyze the data. Bayesian statistics incorporates external domain-knowledge into data analysis via so-called “prior” distribution.
“Frequentists view ‘prior’ as a weakness that can hamper scientific objectivity and can corrupt the final statistical inference,” says Mukhopadhyay. “I could come up with ten different kinds of ‘prior’ if I asked ten different experts. Bayesians, however, view it as a strength to include relevant domain-knowledge into the data analysis.” This has been a disagreement in statistics over the last 250 years.
So, which camp is right? “In fact, both are absolutely right,” says Mukhopadhyay. In their paper, they argued that a better question to ask is, how can we develop a mechanism that incorporates relevant expert-knowledge without sacrificing the scientific objectivity?
The answer, Mukhopadhyay says, can ultimately help design artificial intelligence capable of simultaneously learning from both data and expert knowledge—a holy grail problem of 21st Century statistics and AI.
“The science of data analysis must include domain experts’ prior scientific knowledge in a systematic and principled manner,” Mukhopadhyay says. Their paper presents Statistical rules to judiciously blend data with domain-knowledge, developing a dependable and defensible workflow.
“That is where our breakthrough lies,” says Mukhopadhyay. “It creates a much more refined ‘prior,’ which incorporates the scientist’s knowledge and respects the data, so it’s a compromise between your domain expertise and what the data is telling me.”
Answering that question—when and how much to believe prior knowledge—offers dozens of real-world applications for Mukhopadhyay’s work. For example, healthcare companies can use apply this to new drugs by leveraging doctors’ expertise without being accused of cherry picking data for the sake of a speedy or unusually successful clinical trial.
Mukhopadhyay thanks Brad Efron of Stanford University, for inspiring him to investigate this problem. “It took me one and a half years to come up with the right question,” says Mukhopadhyay. “I believe Bayes and Frequentist could be a winning combination that is more effective than either of the two separately in this data science era.”
*This article corrects an earlier version by specifying that the research was published in Scientific Reports, a journal by Nature Research.
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A team of students from Methacton High School, in Eagleville, Pa., won the Statistics Data Challenge, which pitted 25 teams of four students each in the completion of a written examination that tested their acuity in the areas of statistics and data analytics.
“These skills are the cornerstones of a new undergraduate major we will offer this fall, when we introduce a Bachelor of Science degree program in Statistical Science and Data Analytics,” Fox School Dean M. Moshe Porat said to the student participants. “The demand for undergraduate degrees in statistics is at an all-time high, and is increasing nationally, and we hope you choose Fox to continue your academic careers.”
In addition to the written component, the Statistics Data Challenge also featured a walking tour of Temple’s campus during a lunch-break respite, as well as a few brief presentations from faculty, PhD students, and graduates of the Fox School’s Department of Statistics on the important role of statistics and data analytics in business and industry.
Organized by Dr. Alexandra D. Carides, Assistant Professor of Statistics, in conjunction with the Fox School’s Office of Research, Doctoral Programs, and Strategic Initiatives, the competition’s plans for next year are already in motion.
“This was a great day of intellectual challenge and stimulation, and we look forward to offering an even-higher caliber contest that challenges the region’s brightest high school students – and potentially future Temple students – in statistics next year,” said Carides, who serves as Director of Fox’s newly formed Statistical Science and Data Analytics undergraduate program.
The Fox School of Business at Temple University will introduce new academic programs for the 2016-17 academic year.
A Bachelor of Science program in Statistical Science and Data Analytics headlines the new offerings by the Fox School, and joins two undergraduate minors in Leadership and International Business Administration.
At the graduate level, students can elect for MBA concentrations in either Business Analytics or Enterprise Risk Management. In Fall 2016, Fox also will launch a Master of Science degree program in Business Analytics.
“The addition of new programs and concentrations demonstrate our reputation as one of the nation’s most-comprehensive business schools,” said Dr. M. Moshe Porat, Dean of the Fox School of Business. “Employers and industry partners agree that these areas represent emerging fields and areas of study wherein professionals and leaders are in great demand, and we have the diverse, renowned faculty to answer the call of industry and these support programs.”
The undergraduate major in Statistical Science and Data Analysis will provide students with the ability to select, utilize and apply quantitative reasoning and data analytic skills to their future fields of study, according to program director Dr. Alexandra Carides, Associate Professor of Statistical Science.
The minor in International Business Administration incorporates the nationally ranked curriculum of Fox’s undergraduate-degree program in International Business. The minor requires only four courses and four prerequisites, delivering the cornerstones of international business education while offering students the opportunity to complete a study-abroad trip in the process.
The minor in Leadership cultivates stronger interpersonal skills for effective management and leadership positions. With courses focusing on workplace demands for leadership from both the organizational and interpersonal points of view, the minor allows students to move beyond technical competence as they step into leadership roles in industry.
The MBA concentration in Business Analytics is designed to enable graduate students to use data and models to recognize opportunities and to improve organizational decision-making. “Data-driven decision-making has been shown to have large positive effects on outcomes of interest to organizations of all types,” said Assistant Professor of Marketing and Supply Chain Management Dr. Eric Eisenstein, the concentration’s director. “Business Analytics concentrators will meet the growing demand for talent in the areas of managing, analyzing, predicting, and discovering insights from the complex data that is available to modern corporations.”
The MBA concentration in Enterprise Risk Management, offered by one of the most-prestigious Risk Management programs in the nation, will prepare MBA students to design and implement state-of-the-art processes that enhance and improve organizational strategic decision-making, how it manages risk across the enterprise, as well as improving traditional risk mitigation decisions. “This concentration will provide MBA candidates with the concepts and tools to develop advanced organizational risk management capabilities and pursue executive responsibility for managing enterprise-wide risks,” said Assistant Professor of Risk, Insurance, and Healthcare Management Dr. M. Michael Zuckerman, the concentration’s director.
All eligibility and declaration questions regarding the new undergraduate major and minors should be referred to Fox’s Center for Undergraduate Advising. Graduate students are encouraged to speak with their program advisors for more details about new curricula.
One of the first-established academic departments at Temple University’s Fox School of Business is getting a new name, and is set to introduce a new undergraduate degree program.
The Fox School’s Department of Statistics will soon be rebranded as the Department of Statistical Science. Additionally, the department will unveil a Bachelor of Science degree program in Statistical Science and Data Analytics. Both changes are effective for the 2016-17 academic year, following the approval in March by Temple’s Board of Trustees.
The department had been known as the Department of Statistics since its establishment in 1929, 11 years after the founding of the Fox School.
“Rebranding our department as the Department of Statistical Science reflects the breadth of our department’s academic research, the discipline’s changing landscape, and our department’s renewed focus on engaging in quality research that reshapes the field of statistics and to train new generations of statistically skilled graduates,” said Dr. Sanat K. Sarkar, Chair of the Department of Statistical Science.
The new department name, Sarkar added, is reflective of the discipline’s evolution into one that “develops newer subfields and its interdisciplinary research with scientists in modern scientific investigations involving complex data.”
In Fall 2016, the department will launch its Bachelor of Science undergraduate degree program in Statistical Science and Data Analytics. The demand for the program, said program director Dr. Alexandra Carides, has been driven by the proliferation of computing technology, software, and statistical tools for capturing and interpreting the substantial volume of data now available at the enterprise, government, and personal levels.
The program will qualify students for professions in some of the fastest-growing job sectors, according to Carides.
“The program will provide undergraduate students with the ability to select, utilize, and apply quantitative reasoning and data analytic skills to their future field of study,” said Carides, an Assistant Professor of Statistical Science. “Knowledge of statistical theory and methods has become increasingly important to students in many disciplines. As more data are collected, stored, and analyzed, students are finding it increasingly beneficial to gain expertise in statistical science to strengthen their skills and enhance their career opportunities.”
The 18th annual Innovative Idea Competition used entrepreneurship to unite students across Temple University.
Temple’s Innovation and Entrepreneurship Institute (IEI) hosts the yearly competition, which encourages generation of innovative new products, services, and technologies as the foundation of new businesses. The most-recent competition, held Nov. 12 at Alter Hall and the Fox School of Business, welcomed 351 submissions from 12 different schools and colleges, marking a 39-percent increase in participation from 2014.
The competition not only features interdisciplinary submissions, but also encourages faculty, graduate and undergraduate students to compete for nine awards, said Ellen Weber, IEI’s Executive Director.
“This competition inspires students and demonstrates that entrepreneurship is a viable path,” said Ellen Weber, Executive Director of IEI. “It’s their first toe in the water in terms of getting their ideas out there.”
The Anne Nelson Grand Prize of $2,500 went to Stephen Peduto from the College of Engineering for his venture, Quick Stabilizing Carbon. Peduto’s idea, which earned first place in the Undergraduate track, creates a cast for broken bones that would expedite the healing time.
Entrants from the Fox School of Business received both first and second place in the Graduate, Faculty, Staff or Alumni track. Olawunmi Thomas-Quarcoo, a Fox School MBA candidate, took first place and $500 in prize money for Ka Bom Designs, a platform for female African clothing designers to market their creations. (Quarcoo also took first place and an additional $1,000 in the People’s Choice category.) In the same track, Fox MBA candidate Séverine Bandou earned second place and $500 for Myjé, a hair fragrance for people whose hair texture makes regular washing difficult. Originally from Paris, Bandou came up with the idea to remedy a problem she’s experienced personally.
First place in the Undergraduate category went to Fox School senior Tyler Stoltzfus for Seed Dyes. An Entrepreneurship and Innovation major, Stoltzfus created Seed Dyes as a sustainable textile dye. Taking home the $1000 prize, Stoltzfus’ Seed Dyes appeals to the competition’s social impact element.
Other Innovative Idea Competition winners included:
- Sabrina Zouaghi, from the College of Science and Technology. Her venture, Self-Stabilizing Gloves, would provide a mechanism for stabilizing hand movement in people who suffer from muscle tremors. Zouaghi earned $1,000 for finishing in second place in the Undergraduate track and an additional $500 as the second-place winner in the People’s Choice category.
- Camille Bell, an alumna from the School of Media and Communication. Her venture, Poundcake, provides a line of cake-inspired lipsticks that come in several shades for women of all different skin colors. Bell received $500, in addition to the competition’s Global Innovation prize.
Many of the ventures presented at the Innovative Idea Competition will go on to compete in the IEI’s Be Your Own Boss Bowl (BYOBB) this spring. The BYOBB encourages students to develop a comprehensive business plan and to test the functionality of their idea.
“It’s one thing to have an idea and another to test it,” Weber said. “The Innovative Idea Competition focuses on opportunity recognition and the generation of new, feasible ideas, while the BYOBB focuses on creating the business plans to execute an idea.”