Normal Curves Podcast: Mixing Sexy Science & Serious Statistics

 Imagine sitting in a room crafting a concept for a new podcast. After hours of brainstorming, bad coffee, flaky croissants, and short tempers, the group hits upon an idea that they can move forward with. 

The group decides to "start a podcast with two college professors who are statistics nerds and talk a lot about dissecting data."

 They bring their idea to the boss, who looks like the Community Chest guy in Monopoly, who barks, "Are you kidding me? This will never work. It'll put people to sleep."

 Then you listen to the first episode of Normal Curves and realize how wrong the boss was -- again!

 Normal Curves is a podcast about sexy science & serious statistics. The marketing pitch is a good one: "Ever try to make sense of a scientific study and the numbers behind it? Listen in to a lively conversation between two stats-savvy friends who break it all down with humor and clarity. Professors Regina Nuzzo and Kristin Sainani discuss papers like a journal club does — except with more fun, less jargon, and some irreverent, PG-13 content sprinkled in. Join Kristin and Regina as they dissect the data, challenge the claims, and arm you with tools to assess scientific studies on your own."

Before we get into the essence of the show, let me tell you about these "geeky" hosts.

Kristin Cobb Sainani is a Professor at Stanford University and Freelance Science Writer. She is a Stanford professor and science journalist who brings statistics and scientific writing to students and audiences worldwide. She teaches the popular Coursera course Writing in the Sciences, available in 22 languages, and offers an online medical statistics certificate program through Stanford Online.

Kristin works as a statistician on sports medicine projects and serves as a statistical or associate editor for academic journals, including Medicine & Science in Sports & Exercise, Sports Medicine, and The American Journal of Sports Medicine.

Kristin has also written extensively about health, science, and statistics for diverse audiences. She authored a health column for Allure magazine, a beauty magazine, for ten years and authored a statistics column, along with co-host Regina Nuzzo, for the journal Physical Medicine & Rehabilitation for over a decade. In 2018, she received the Biosciences Award for Excellence in Graduate Teaching at Stanford University. Known for her statistical sleuthing and ability to cut through academic jargon, she champions sound statistics and clear language in science.

 Regina Nuzzo is a Professor at Gallaudet University and Freelance Science Writer. Regina is an award-winning science journalist and Gallaudet University professor, who talks to audiences around the world about communicating statistics creatively. She’s written for Nature, New York Times, Reader’s Digest, Scientific American, New Scientist, Science News, and ESPN the Magazine, among others, including a column about the science of sex, dating, and relationships for the Los Angeles Times.

Regina's feature article on p-values in Nature earned the American Statistical Association’s 2014 Excellence in Statistical Reporting Award. Along with co-host Kristin Sainani, she wrote a statistics column for the journal Physical Medicine & Rehabilitation for several years, and she formerly served as a writer for the Proceedings of National Academy of Sciences and for the American Statistical Association.

Since 2022, Regina has also been a summer Lecturer at Stanford University, where she and Kristin teach a statistics course for clinical informatics management graduate students. In her lectures and teaching, Regina often incorporates sex-science examples to keep her audiences awake, and professes no shame in doing so.

The real question is: Can these two college professors be interesting podcast co-hosts? The answer is an unqualified yes. Perhaps it is the years of lecturing students, but the co-hosts are comfortable in front of a mic.

Dr. Kristin and Dr. Regina live up to their marketing promise and make the show fun, funny, and a painless way to learn more about data and statistics.

The show began in February with the requisite trailer and then a short, introductory episode of 13 minutes about the show and themselves.

Their first episode was promising and entertaining. The episode pulled the curtain back on sweaty t-shirt dating parties, sex pheromone dating sites, and choosing your dating partner by sniffing them up. Then, the two professors asked if these are wacko fringe fads or evidence-based mating strategies? And what does your armpit stain have to do with your kids’ immune systems, or hormonal contraceptive pills, or divorce rates? 

In this episode, Dr. Kristin and Dr. Regina reach back into the 1990s and revisit the scientific paper that started it all: The Sweaty T-Shirt Study. They bring a sharp eye and open mind, critically examining the study and following the line of research to today. Along the way, they encounter interesting statistical topics—including correlated observations, within-person study design, and bar-chart blasphemy—with a short, surprising detour into Neanderthal sex. 

It was an enjoyable show, and as a plus, I know something about correlated observations. In the third episode, the professors chat about how wearing red drives men wild with lust – or so says scientific research on color’s role in human mating. But can a simple color swap really boost a woman’s hotness score? In this episode, the professors delve into the evidence behind the Red Dress Effect, from a controversial first study in college men to what the latest research says about whom this trick might work for (and who it might not).

Along the way, the co-hosts encounter red monkey butts, old-Internet websites, the Winner’s Curse in scientific research, adversarial collaborations, and why size (ahem, sample size) really does matter. 

Statistical topics in the show include reproducibility crisis in psychology, sample size, selection bias, winner’s curse, Cohen’s d standardized effect size, adversarial collaboration, meta-analysis, preregistration, publication bias, and statistical moderators.

 I highly recommend Normal Curves. The show tweaks the usual informational podcast format, adding science with a beaker full of fun, and frictionless learning about statistics.