Stats + Stories

Over the course of the last year, statistics have framed our lives in very obvious ways. From COVID cases to unemployment rates, stats have helped us understand what’s happening in the wider world. As we contemplate how to “build back better” in the aftermath of the pandemic, official statistics could help guide our way, at least, that’s what the authors of a recent Significance Magazine article think. That’s the focus of this episode of Stats and Stories with guest Paul Allin. Paul is a visiting professor of statistics in the department of mathematics at Imperial College London, UK. His research interests are the measurement of national wellbeing and progress, and the use of these measures in politics, policy, business, and everyday life. He also chairs the Statistics User Forum, an ‘umbrella’ organization that brings together producers and groups of users of UK official statistics. Paul previously spent forty years as a professional statistician, researcher, and policy analyst in the Office for National Statistics and other departments and agencies, including as the director of the Measuring National Wellbeing program. His social media usage is limited to LinkedIn and StatsUserNet.

For years now, the utility of the P-value in scientific and statistical research has been under scrutiny – the debate shaped by concerns about the seeming over-reliance on p-values to decide what’s worth publishing or what’s worth pursuing. In 2016 the American Statistical Association released a statement on P-values, meant to remind readers that, “The P-values was never intended to be a substitute for scientific reasoning.” The statement also laid out six principles for how to approach P-values thoughtfully. The impact of that statement is the focus of this episode of Stats and Stories with guest Robert Matthews. Robert Matthews is a visiting professor in the Department of Mathematics, Aston University in Birmingham, UK. Since the late 1990s, as a science writer, he has been reporting on the role of NHST in undermining the reliability of research for several publications including BBC Focus, and working as a consultant on both scientific and media issues for clients in the UK and abroad. His latest book, Chancing It: The Laws of Chance and How They Can Work for You is available now.  His research interests include the development of Bayesian methods to assess the credibility of new research findings – especially “out of the blue” claims; A 20-year study of why research findings fade over time and its connection to what’s now called “The Replication Crisis”; Investigations of the maths and science behind coincidences and “urban myths” like Murphy’s Law: “If something can go wrong, it will”; Applications of Decision Theory to cast light on the reliability (or otherwise) of earthquake predictions and weather forecasts; The first-ever derivation and experimental verification of a prediction from string theory.

Every two years the International Prize in Statistics is given out to recognize an individual or team for major contributions to the field of statistics particularly those that have practical applications or which lead to breakthroughs in other disciplines. The winner is chosen in a collaboration between the American Statistical Association, the Institute for the Mathematical Sciences, the International Biometric Society, the International Statistical Institute, and the Royal Statistical Society. The 2021 honoree is Nan Laird and her award and career is the focus of this episode of Stats and Stories. Laird is the Harvey V. Fineberg Professor of Biostatistics at Harvard University. During her more than forty years on the faculty, she developed many simple and practical statistical methods for pressing public health and medical problems. Her work on the EM Algorithm, with Art Dempster and Don Rubin, is among the top 100 most cited of all published articles in science. She’s also developed popular and widely used methods for meta-analysis, longitudinal data, and statistical genetics. She has worked in several areas of application including the quantification of adverse events in hospitals, childhood obesity, and genetic studies in Alzheimer’s disease, bipolar disorder, asthma, and lung disease. Laird was awarded the 2021 International Prize in Statistics for, "her work on powerful methods that have made possible the analysis of complex longitudinal studies."

The universe seems unbelievably vast, a sky filled with countless stars and worlds. Well, maybe not so countless as there’s a whole field devoted to crunching the numbers associated with an ever-expanding universe. Astrostatistics is the focus of this episode of Stats and Stories Jessi Cisewski-Kehe is an assistant professor in the Department of Statistics at the University of Wisconsin-Madison. Her research focuses on methodological development for complicated datasets of which closed-form models and likelihood functions are not able to fully capture the desirable and interesting features of the observations. Statistical challenges in astronomy, astrophysics, and cosmology (i.e., astrostatistics) are a primary focus of her work. Chad Schafer is a professor in the Department of Statistics & Data Science at Carnegie Mellon University. Since his Ph.D. work at the University of California at Berkeley, he has worked on statistical challenges that arise in astronomy, with a particular focus on the handling of complex estimation problems. He is currently involved with the Legacy Survey of Space and Time, to be conducted at the under-construction Vera C. Rubin Observatory, co-chairing its Informatics and Statistics Science Collaboration since 2015.

Enter with your meme for a chance to appear on the show. All entries are submitted through Twitter through the official Stats+Stories account (https://twitter.com/statsandstories) by July 10th for entry.

Where are the best locations for food pantries? What are the patterns and use of a crisis call center? How can services be improved for the senior population of Wahtenaw County in Michigan? These questions share a common denominator, they represent data and analysis needs of community service organizations. Statistics in the service of the community is the focus of this episode of Stats and Stories with guests. Emily Morris and Tom Braun. Tom Braun is a Professor in the Department of Biostatistics and has been a faculty advisor for STATCOM for the past three years. Dr. Braun is an international expert in the design of Bayesian adaptive designs for oncology clinical trials, and he has more recently expanded his research into snSMART designs for clinical trials for rare diseases. Dr. Braun has collaborated with a variety of medical and public health investigators, including bone marrow transplantation, cancer of the mouth, breast, and lungs, periodontal disease, and development of anthrax vaccines. Tom also is an active member in University of Michigan committees working to address issues of incivility, rankism, and harassment in academia, and he also active in developing new pedagogy for teaching biostatistics and data science. Emily Morris is a PhD candidate in the Department of Biostatistics and former co-president of Statistics in the Community (STATCOM) at the University of Michigan. In addition to the leadership role, her involvement in STATCOM projects ranges from summarizing patterns in counseling visits at a local nonprofit to identifying optimal locations for mobile food pantries in Toledo. Her research primarily involves machine learning methods applied to brain imaging analysis.

Big data, though not new, is often talked about as though it is. It’s become something of a buzzword associated with everything from politics to record sales to epidemiology. But, not all big data is created the same – some of it might not even be that big at all. That’s the focus of this episode of Stats and Stories with guest Xiao-Li Meng Xiao-Li Meng is the Whipple V. N. Jones Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review, is well known for his depth and breadth in research, his innovation and passion in pedagogy, his vision and effectiveness in administration, as well as for his engaging and entertaining style as a speaker and writer. Meng was named the best statistician under the age of 40 by COPSS (Committee of Presidents of Statistical Societies) in 2001, and he is the recipient of numerous awards and honors for his more than 150 publications in at least a dozen theoretical and methodological areas, as well as in areas of pedagogy and professional development.

Parents, educators, and activists have all raised concerns about the impact of COVID on the educational experience of students. For high school students, these issues are amplified as they consider graduation and what may come after. The impact of COVID on high school grades is a focus of this episode of Stats and Stories with guest Harrison Schramm. Harrison Schramm is a Principal Research Scientist at Group W as well as President-Elect at the Analytics Society of INFORMS.  Prior to joining INFORMS he was a Senior Fellow at Center For Strategic And Budgetary Assessments and has been a leader in the Operations Research community for the past decade. Before that, he had a successful career in the US Navy, where he served as a Helicopter Pilot, Military Assistant Professor at the Naval Postgraduate School, and as a lead Operations Research Analyst in the Pentagon. His areas of emphasis were large-scale simulation models, statistics, optimization, and applied probability. His research interests lie at the intersection of data and mathematical models.

Our modern understanding of big data and the increasingly sophisticated tools we have for analyzing them have opened up whole new worlds for exploration. And, sometimes, whole new avenues for the misuse of data, which has led some to wonder who should be responsible or held accountable for data misuse or data bias? That’s the focus of this episode of Stats and Stories with Charna Parkey. Dr. Charna Parkey is a lead data scientist at Kaskada, where she works on the team to deliver a commercially available data platform for machine learning. Her interests include analysis of different language patterns as well as using data science to combat systemic oppression. She has over 15 years’ experience in enterprise data science and adaptive algorithms in the defense and startup tech sectors and has worked with dozens of Fortune 500 companies in her work as a data scientist.

It’s been a little over a year of lockdowns, curfews, online schooling, mask wearing, worry and grief. The COVID-19 pandemic has brought with it an experience of collective trauma that researchers will be studying for years to come. The British Academy has launched one such study COVID119 and Society: Shaping the COVID Decade. That’s the focus of this episode of Stats and Stories with guest Dr. Molly Morgan Jones. Dr. Molly Morgan Jones is the Director of Policy at The British Academy. She oversees all the Academy’s policy work and activities, on topics ranging from how the humanities and social sciences can shape a post-pandemic future, to purposeful business, cohesive societies, policies supporting childhood, and higher education and skills policy. Prior to joining the Academy, she worked at RAND Europe, an independent policy research institute, where she specialized in research and innovation policy as well as worked for the UK Department for Environment, Food and Rural Affairs (Defra) and for the U.S. Food and Drug Administration (FDA).