According to the World Bank, some 3.5 billion people live on less than $7 a day. That's more than 40% of the global population. Almost 700 million of those individuals live in extreme poverty, getting by on less than $2.15 a day. In the US in 2024, almost 40 million Americans were living in poverty, according to the U.S. Census. But what do all these numbers mean? How do the people researching income inequality measure poverty, and how reliable are those measurements? That's the focus of this episode of Stats and Stories with guest David Johnson.

David Johnson is the executive director of the International Association for Research in Income and Wealth. Prior to that, he served as a study director for the National Academies of Sciences, Engineering and medicine, for a report called, "Creating an integrated system of data and statistics on household income, consumption and wealth.". Johnson also served for 25 years in the Federal Statistical system, where he was the only senior executive to have leadership roles at the Bureau of Labor Statistics, the Bureau of Economic Analysis and the US Census Bureau. At the Census, he led the implementation of the supplemental poverty measure and the reengineering of the Survey of Income and Program Participation.

Dr. Lloyd Edwards is Professor and Chair of Biostatistics at the University of Alabama at Birmingham. Dr. Edwards has an extensive background in collaborating with researchers in a broad range of areas in biomedical research, including cardiovascular disease, cystic fibrosis, cancer, aging, pediatrics, and minority health. His primary area of applied statistical research relates to the analysis of longitudinal data. Specifically, his statistical research includes derivation of techniques for computation of power, control of Type I error, and measuring model fit in linear and generalized linear mixed models.

Television is filled with "will they or won't they" couples. Friends had Ross and Rachel. Parks and Rec had Leslie and Ben. The Gilmore Girls, had Lorelei and Luke. But what happens after the couple's kiss? Do we keep watching? One statistician dug into the data behind the kiss effect, and that's the focus of this episode of Stats and Stories with guest Ashley Mullan. 

Ashley Mullan is a PhD student and research assistant in Vanderbilt University's Department of biostatistics. Currently, Mullan works on a team focusing on the care children receive in Tennessee's child welfare and juvenile justice systems. She's also interested in pop culture, and in her spare time, analyzes her own consumption of popular media. That led Mullan to author a Significance article on The Kiss Effect, the impact of a "will they won't they?" couple's first kiss on a TV show's ratings.

Peter Guttorp (@pgseattle) is a Professor at the Norwegian Computing Center in Oslo, Norway, and Professor Emeritus at the University of Washington, Seattle. He is also a vice-president of the International Statistical Institute . His research focuses on stochastic models of scientific data and their statistical analysis. He has worked in seismology, hydrology, climatology, hematology and biology.

When it comes to studying conflict, there is obvious data to examine: spending on arms, the number of people killed or injured, and the amount of land won or lost. What's harder to track are the indirect effects of conflict, the ways it produces deaths over time, or its impacts on public health. Researchers are trying to find ways to account for the sometimes less obvious impacts of conflict, and that's the focus of this episode of Stats and Stories with guest Xiao Hui Tai.

Xiao Hui Tai is an assistant professor of statistics at the University of California Davis' Department of Statistics. Her research interests include the use of non-traditional data sources to study problems in data-scarce settings. With the current focus on global public health and estimating the consequences of violent conflict, she's the author of the Significance article Counting the True Cost of War.

Hybrid cars are everywhere now but what is your best option if you want to feel the wind in your hair, or at least under your helmet and you want to get a little exercise as well? Well, e-bikes are an answer and that’s the topic on this episode of Stats + Short Stories with guest Helaine Alessio.

Helaine Alessio, PhD, FACSM is a Professor and Chair of the Department of Kinesiology, Nutrition, and Health at Miami University and is a past President of the MWACSM and a fellow of the American College of Sports Medicine. She teaches Exercise Science-related courses and has received university commendations for her teaching. She has been funded by NIH, private foundations, and corporations to support research, teaching, and service projects. She has published 2 books, 13 book chapters, and 56 journal articles, as well as national and international peer reviewed blogs, infographics, and NPR broadcasts. She is listed in the top 2% of Exercise Scientists cited in the world by Stanford University researchers. Her work on academic integrity includes co-editing a special edition of a journal on the topic that was the most widely published for the Journal of Excellence in College Teaching.

The Billboard Hot 100 has been ranking the week's most popular music since 1958. The first song to top the chart was Ricky Nelson's Poor Little Fool. The most recent song to do so is Taylor Swift's The Fate of Ophelia. A lot has changed in the music industry between those two songs, not only in the types of songs that top the charts, but also in how they're promoted and how they're determined. A new book explores the statistics behind the Hot 100, and it's the focus of this episode of Stats + Stories with guest Chris Dalla Riva.

Chris Dalla Riva is an analyst for the music streaming service Audiomack by day while spending his nights writing and recording music and writing about music for his newsletter Can’t Get Much Higher.

On the podcast, we talk about the ways we live in and with data, as well as the ways data shape our lives and our politics. Public discourse around data is often wrapped up in the negative ways it can impact our lives. A movement among statisticians, data scientists, and other researchers shows the positive impacts of data when used to work towards solutions to humanitarian problems. The data for good movement is a focus of this episode of Stats and Stories with guest David Corliss.

David Corliss is the founder and director of Peace Work, a volunteer cooperative of statisticians and data scientists applying statistical methods to issue-driven advocacy. Human trafficking research is a major initiative at Peace Work. Corliss is also a research scholar and a member of the Global Association of Human Trafficking Scholars.

Glenn Platt (@glennplatt) is the C. Michael Armstrong Professor of Network Technology & Management & Director of Interactive Media Studies at Miami University. He is interested in social media marketing, digital media and e-Commerc. He is also the faculty sponsor of the Esports team at Miami.

American Football is a game played with 11 players on offense competing against 11 players on defense, with a sequence of plays executed as one team attempts to outscore the other, but each discrete play reflects actions on the field by players and off the field by coaches. For example, what is the best spot on the field to complete a pass and not get it intercepted? How do quarterbacks differ with respect to their release points? When should you ice the kicker? These are the questions that we are trying to answer on this special football-themed episode of Stats+Stories. 

Mike Lopez serves as Senior Director of data and analytics at the National Football League, and he's held this position since August of 2018, after previously serving as director in the same department. Before this role, Mike worked at Skidmore College as a lecturer, research associate and as an assistant professor.

Adriana Gonzalez Sanchez is pursuing a PhD in business analytics from the University of Cincinnati, with a research focus on discrete data analysis and statistical methodology.

Ryan Elmore is an associate professor in the Department of Business Information and Analytics at the University of Denver's Daniel College of Business. His research interests include statistics and sports, non-parametric statistical methods, and energy-efficient high-performance computing. He currently serves as an associate editor for the Journal of Quantitative Analysis in Sports.

Background in Sports Analytics 2:00

Evolution of Football Data 5:23

2024 Kickoff Rule Changes 8:36

Next Generation Stats and Data Collection 15:28

In-Game Analytics and Coaching Decisions 20:35

Fourth Down Strategy Revolution 24:23

Future of Player Evaluation 27:20

Replay Process Efficiency 28:30

Ryan Elmore and Adriana Gonzalez Sanchez Interview Starts 31:50

Inspiration for the Research 33:23

Play-by-Play Data 37:53

Defining Iced Kicks & Matching Approach 40:33

Causal Inference & “Parallel Universes” Idea 45:05

Strategic Use of Timeouts & Other Situations 51:03

Future Research Directions 57:25