Normal Curves: Sexy Science, Serious Statistics

A famous Harvard researcher. A blockbuster finding about honesty. Suspicious data, failed replications, and a $25 million lawsuit. Welcome to one of the strangest research misconduct scandals in recent memory. In the first of two episodes about the Francesca Gino case, we investigate a famous experiment claiming that signing an honesty pledge at the top of a form makes people less likely to cheat....

Can you spot problems in a scientific study just by reading the published paper? We put our statistical sleuthing skills to the test with a famous study on procrastination and deadlines that was retracted more than 20 years after it was published. But were there clues hidden in plain sight in the published results—and would we have noticed anything suspicious at the time? We put on our data-detect...

What happens when you discover that your published paper is wrong? Does retracting it ruin your reputation—or could owning the mistake actually make things better? In this episode, we meet the inaugural winners of the Ctrl-Z Awards, which recognize scientists for correcting or retracting their own work. Behavioral ecologist Kate Laskowski takes us inside a scientific detective story involving susp...

Statistical power is one of the most important ideas in statistics—and one of the most misunderstood. In this episode, we explain what statistical power really means, why researchers need to think about it before they collect their data, and what goes wrong when they calculate “post hoc power” after the study is over. Along the way, we hunt for UFOs, test Kristin’s psychic abilities, explore the e...

Can weed protect your brain as you get older? We unpack a study linking lifetime cannabis use to larger brain volumes and better cognitive test scores in older adults—and investigate how those findings became headlines urging readers to “pass the pot to grandma.” Along the way, we explore collapsing categorical variables, confounding, clinically versus statistically significant results, multiple t...

Can the meningitis vaccine do double duty against gonorrhea? We examine a fascinating randomized trial inspired by years of encouraging observational studies—and what happened when those earlier results were finally put to the test. Along the way, we discuss ecological studies, case-control studies, why statisticians distrust phrases like “trend toward significance,” how intention-to-treat differs...

Can you improve your endurance by sitting in a hot tub instead of doing another hard workout? We dig into a study that put elite runners through five weeks of what we affectionately call “ endurance hot tubbing” to see whether heat alone could trigger the same cardiovascular adaptations as altitude training. Along the way, we explore crossover study designs, multiple testing, why significant physi...

Could four one-minute bursts of exercise really improve blood sugar? We try “exercise snacks” ourselves before taking a close look at the clinical trial that inspired headlines. We explain why the study’s main result wasn’t statistically significant, how 34 secondary outcomes complicated the story, and what pre-registration can reveal about a study after it’s published. Along the way, we compare n...

How do you decide whether a clinical trial “worked”? In Part 2 of our Galleri series, we examine the landmark randomized trial of a blood test designed to detect more than 50 cancers. We explore why different outcome measures led to dramatically different headlines, discuss primary versus secondary outcomes, pre-registration, hierarchical testing, and post hoc analyses, and explain why mortality r...

Can a single tube of blood really detect dozens of cancers before symptoms appear? We dive into the science behind Galleri, a blood test that claims to detect more than 50 types of cancer from a simple blood draw. Recent headlines about the test ranged from “breakthrough” to “bust” after the release of results from a massive randomized clinical trial. In this Part 1 episode, we explore cell-free D...

Odds ratios show up everywhere in medical research—but do readers, journalists, and even researchers always know what they mean? In this episode, we tackle one of the most common statistical misunderstandings in science: treating odds ratios like risk ratios. Along the way, we explore puppy photos, fish photos, first-date hookups, sugary drinks, cardiac care, and a listener challenge that started...

Does coffee trigger atrial fibrillation — or have doctors been warning people away from caffeine without strong evidence? We dig into two recent randomized clinical trials testing whether caffeinated coffee causes dangerous heart rhythm problems. Along the way, we talk about AFib, survival analysis, intention-to-treat versus as-treated analyses, and one surprisingly elaborate effort to catch clini...

Can exercise actually be bad for you if you don’t get enough sleep? A widely shared claim says yes—that working out while sleep deprived may speed up aging. In this episode, we put that claim under the microscope. We examine the study behind it, unpack how sleep and aging were measured, and explore key statistical ideas like interaction effects and flexible models that can “dance” to the data. Wit...

Are young people really having less sex? Headlines about a “sex recession” suggest a dramatic decline—but what do the data actually show? In this episode, we trace that claim back to the research behind it—and find a story that’s far more nuanced than the headlines suggest. We examine large national surveys, including the General Social Survey and the National Survey of Sexual Health and Behavior,...

Diagnostic testing: what do those statistics actually tell you? Sensitivity, specificity, positive predictive value . . . you’ve probably seen these terms before. Maybe you memorized them for a test. But do you actually know what they mean? In this episode, we take a closer look at how diagnostic tests are evaluated—and how they’re often misinterpreted. From a genetic test for cellulite to a blood...

Epidurals are widely used and widely trusted for pain relief during labor. So when a 2020 study reported that they might be linked to autism, it raised a troubling question: could a routine medical decision have long-term consequences? We follow that claim from headline to evidence—and watch what happens when other scientists take a closer look. We dig into the original study, a wave of replicatio...

Every year we spring forward and lose an hour of sleep. But do we also lose a few heart cells? Some headlines claim that heart attacks spike by 24% after daylight saving time begins. In this episode we trace that number back to the research behind it—and what we find is more complicated than the headlines suggest. We examine a famous New England Journal of Medicine letter, a large international me...

How many carbs do you need to run your best marathon? Recent headlines suggest that 120 grams per hour is the magic number. But what’s the science behind that claim? To find out, we dug into the study fueling the hype — and were surprised by what we found. In this episode, we uncover numbers that mysteriously shift after peer review, figures that don’t match the text, and p-values that refuse to l...

Can a list of questions really make two strangers fall in love? In 2015, a viral New York Times Modern Love column claimed psychologists had discovered a formula for love: 36 increasingly personal questions, plus four minutes of eye contact. Millions of people tried it. There was even an app. But when we followed the citation trail back to the science, the story started to unravel. In this episode...

While we’re on a short break between seasons, we’re revisiting some of our favorite episodes from Season 1. This week, we’re re-releasing our debut episode on pheromones and sexy sweat, with some added commentary up front.. Sweaty t-shirt dating parties, sex pheromone dating sites, choosing your dating partner by sniffing them up — wacko fringe fads or evidence-based mating strategies? And what do...

While we’re on a short break between seasons, we’re revisiting some of our favorite episodes from Season 1. This week, we’re re-releasing our exploration of how your diet can affect your skin – now with added commentary! Wrinkles and sagging skin—just normal aging, or can you blame your sweet tooth? We dive into “sugar sag,” exploring how sugar, processed foods, and even your crispy breakfast toas...

While we’re on a short break between seasons, we’re revisiting some of our favorite episodes from Season 1. This week, we’re re-releasing our deep dive into vitamin D and the origins of the so-called deficiency epidemic, with added commentary. Is America really facing an epidemic of vitamin D deficiency? While this claim is widely believed, the story behind it is packed with twists, turns, and som...

Description Nobody expects Batman—but when he shows up in a crowded subway car, are people suddenly more likely to help a passenger in need? This week on Normal Curves, we unpack a recent quasi-experimental field study involving a caped superhero costume, a prosthetic pregnancy belly, and some puzzled Italian commuters. Along the way, we demystify three common ways of describing effects for binary...

Does the temperature of your coffee six months ago really predict whether you feel gassy today? This week we dissect a new nutrition survey study on hot and cold beverage habits that claims to connect drink temperature with gut symptoms, anxiety, and more—despite relying on year-old memories and a blizzard of statistical tests. It’s the perfect case study for our Holiday Survival Guide Part 2, whe...

Does a little alcohol really make you speak a foreign language better? This week we unpack a quirky randomized trial that tested Dutch pronunciation after a modest buzz—and came to the opposite conclusion the researchers expected. We use it as the perfect holiday case study: instead of arguing with Uncle Joe at the dinner table, we’ll show you how to pull apart a scientific headline using a friend...