Normal Curves is a podcast about sexy science & serious statistics. 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 of Gallaudet University and Kristin Sainani of Stanford University discuss academic papers journal club-style — 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.
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Pheromones: Is sexy sweat the key to genetic diversity?
Episode 2
Monday, February 24, 2025 • Duration 57:54
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 does your armpit stain have to do with your kids’ immune systems, or hormonal contraceptive pills, or divorce rates?
In this episode of Normal Curves, Kristin and 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.
Statistical topics
Correlated observations
Within-person study design
Bar charts
Data and methodological transparency
Cherry-picking
Meta-analysis
Multiple testing
Post-hoc analyses
Methodological morals
“Repeat after me: Bar charts are not for numerical data.”
“Those who ignore dependencies in their data are destined for flawed conclusions.”
(35:22) - Analyzing the Study's Questionable Results
(38:18) - The Pill's Influence on Scent Preferences
(41:26) - Overstated Conclusions and Wandering Discussions
(46:09) - Media Reactions and the Study’s Public Impact
(52:22) - Other Studies and their results
(55:01) - Conclusion
Normal Curves: Who are we and what is this podcast about?
Episode 1
Monday, February 17, 2025 • Duration 13:31
Welcome to a lively conversation about science that's like a journal club, but with less jargon, more fun, and a touch of PG-13 flair. In this introduction, Professors Regina Nuzzo and Kristin Sainani share how they met in graduate school, what they’ve been doing since then, how they’ll choose edgy topics and journal articles to dissect, and a bit about what makes them tick. Join them for their fresh, engaging take on scientific studies, data analysis, and statistical sleuthing.
Normal Curves is a podcast about sexy science & serious statistics. 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 of Gallaudet University and Kristin Sainani of Stanford University discuss academic papers journal club-style — 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.
Vitamin D Part 2: Good for more than just your bones?
Episode 4
Monday, March 24, 2025 • Duration 01:09:19
Can you really sit on your couch, pop vitamin D pills, and shave seconds off your 5k? Touted as a miracle cure-all, vitamin D is claimed to slash cancer and infection risks while boosting mood, cognition, and athletic performance. But does upping your vitamin D really make you healthier and happier? In this episode, we’ll follow the epidemiologic evidence—from clues in petri dishes through randomized trials. Along our journey, we’ll encounter chocolate-fueled Nobel Prizes, rock stars, pasty Brits, and a tangled mess of promiscuous variables.
Statistical topics
ecological studies
ecological fallacy
correlation is not causation
observational studies
statistical adjustment
confounding
randomized trials
factorial design
post-hoc analyses
subgroup analyses
Methodologic morals
“Variables with too many entanglements make observational studies a fool’s game.”
“If your intervention works only when you torture your data, it’s probably a false confession.”
Vitamin D Part 1: Is the Deficiency Epidemic Real?
Episode 3
Monday, March 10, 2025 • Duration 01:23:09
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 some pesky statistical cockroaches. In this episode, we’ll dive into a study on Hawaiian surfers, expose how shifting goalposts can create an epidemic, tackle dueling medical guidelines, and flex our statistical sleuthing skills. By the end, you might wonder if the real deficiency lies in the data.
Statistical topics
dichotomization
normal distribution
standard deviation
researcher biases
conflicts of interest
statistical sleuthing
Methodologic morals
“Arbitrary thresholds make for arbitrary diseases.”
“Statistical errors are like cockroaches: Where there’s one, there’s many.”
Note that all blood vitamin D levels discussed in the podcast are 25-hydroxyvitamin D levels given in units of ng/ml. To convert from ng/ml to nmol/L, use the formula: nmol/L=2.5*ng/ml. For example, a vitamin D level of 30 ng/mL corresponds to 75 nmol/L.
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 toast might be making you look older than if you’d said no to chocolate cake and yes to broccoli. Along the way, we encounter statistical adjustment, training and test data sets, what we call “references to nowhere,” plus some cadavers and collagen. Ever heard of an AGE reader? Find out how this tool might offer a sneak peek at your date’s age—and maybe even a clue about his… um… “performance.”
Statistical topics
Training and test sets
Statistical adjustment
Overfitting
Plagiarism
Proper citing practices
References to nowhere
Methodologic morals
“When you plagiarize, you steal the errors too.”
“Overdone statistical adjustment is like overdone photo filters–at a certain point it’s just laughable.”
What if you could treat your prediabetes with . . . worms? Regina and Kristin dive into a surprising early-phase clinical trial on hookworm therapy—that’s right, intentionally infecting yourself with parasitic worms—to treat metabolic conditions. They dig into the biological rationale (inflammation, abdominal fat, and gut immunology), the clever study design (hello, Tabasco sauce!), and the statistical chops behind this phase 1B trial (block randomization, missing data, and nonparametric hypothesis tests). Along the way, expect self-experimenting scientists, worm sex, poop analysis, and the world’s nerdiest aphrodisiac: a well-documented protocol.
Statistical topics
Randomized controlled trial (RCT)
Primary and secondary outcomes
Placebos, placebo effect, and nocebo effect
Block randomization
Sample size
Double-blinding
Missing data protocols
Reproducible research
Nonparametric hypothesis testing
Kruskal-Wallis test
Methodological morals
“Walk before you can run. Invest in simple but high-quality Phase I clinical trials.”
“When faced with small samples, you better rank and sum, baby.”
Does a daily glass of wine really keep the cardiologist away? It’s a claim we’ve all heard: light to moderate drinking is good for your heart. But is it science or just a convenient excuse for happy hour? In this episode, we dive into the history behind this claim, discuss the challenges of observational studies and statistical adjustment, and explore attempts at randomized trials and natural experiments to get to the bottom of this boozy debate. Grab your drink—or maybe don’t—and join us!
Statistical topics
Statistical Adjustment
Regression
Residual and Unmeasured Confounding
Randomized Trials
Multiple Testing
Outcome Switching
Mendelian Randomization
Methodological morals “Statistical adjustment cannot erase all confounding.”
“When you can’t experiment on people, let Nature experiment on people.”
Wear red and drive 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, we delve into the evidence behind the Red Dress Effect, from a controversial first study in college men to what the latest research says about who this trick might work for (and who it might not). Along the way we 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
Reproducibility crisis in psychology
Sample size
Selection bias
Winner’s curse
Cohen’s d standardized effect size
Adversarial collaboration
Meta-analysis
Preregistration
Publication bias
Statistical moderators
Methodological morals
“The smaller the sample, the flashier the result, the less you should trust it.”
“Good scientists learn from their statistical mistakes and fix them.”
Dating Wishlists: Are we happier when we get what we want in a mate?
Episode 12
Monday, July 14, 2025 • Duration 01:05:31
Loyal, funny, hot — you’ve probably got a wish list for your dream partner. But does checking all your boxes actually lead to happily ever after? In this episode, we dive into a massive global study that put the “ideal partner” hypothesis to the test. Do people really know what they want, and does getting it actually make them happier? We explore surprising statistical insights from over 10,000 romantics in 43 countries, from mean-centering and interaction effects to the good-catch confounder. Along the way, we dig into dessert metaphors, partner boat-count regression models, and the one trait that people say doesn’t matter — but secretly makes them happiest.
Statistical topics
Regression
Random Slopes and Intercepts (Random Effects) in Regression
Standardized Beta Coefficients in Regression
Interaction Effects in Regression
Mean Centering
Exploratory Analyses
Methodological morals
“Good science bares it all.”
“When the world isn't one size fits all, don't fit just one line; use random slopes and intercepts.”
References
Eastwick PW, Sparks J, Finkel EJ, Meza EM, Adamkovič M, Adu P, Ai T, Akintola AA, Al-Shawaf L, Apriliawati D, Arriaga P, Aubert-Teillaud B, Baník G, Barzykowski K, Batres C, Baucom KJ, Beaulieu EZ, Behnke M, Butcher N, Charles DY, Chen JM, Cheon JE, Chittham P, Chwiłkowska P, Cong CW, Copping LT, Corral-Frias NS, Ćubela Adorić V, Dizon M, Du H, Ehinmowo MI, Escribano DA, Espinosa NM, Expósito F, Feldman G, Freitag R, Frias Armenta M, Gallyamova A, Gillath O, Gjoneska B, Gkinopoulos T, Grafe F, Grigoryev D, Groyecka-Bernard A, Gunaydin G, Ilustrisimo R, Impett E, Kačmár P, Kim YH, Kocur M, Kowal M, Krishna M, Labor PD, Lu JG, Lucas MY, Małecki WP, Malinakova K, Meißner S, Meier Z, Misiak M, Muise A, Novak L, O J, Özdoğru AA, Park HG, Paruzel M, Pavlović Z, Püski M, Ribeiro G, Roberts SC, Röer JP, Ropovik I, Ross RM, Sakman E, Salvador CE, Selcuk E, Skakoon-Sparling S, Sorokowska A, Sorokowski P, Spasovski O, Stanton SCE, Stewart SLK, Swami V, Szaszi B, Takashima K, Tavel P, Tejada J, Tu E, Tuominen J, Vaidis D, Vally Z, Vaughn LA, Villanueva-Moya L, Wisnuwardhani D, Yamada Y, Yonemitsu F, Žídková R, Živná K, Coles NA.. J Pers Soc Psychol. 2025 Jan;128(1):123-146. doi: 10.1037/pspp0000524
Apple Podcasts
🇬🇧 Great Britain - science
15/09/2025
#76
🇬🇧 Great Britain - science
14/09/2025
#56
🇬🇧 Great Britain - science
13/09/2025
#44
🇬🇧 Great Britain - science
12/09/2025
#22
(00:00) - Introduction to Normal Curves
(03:49) - How We Met and Our Lasting Friendship
(05:24) - Career Paths
(08:07) - The Art of Evaluating Scientific Studies
2023 review article: Zgutka K, Tkacz M, Tomasiak, et al. A Role for Advanced Glycation End Products in Molecular Ageing. Int J Mol Sci. 2023; 24: 9881. Sentence: “Interestingly, strict control of blood sugar for 4 months reduced the production of glycosylated collagen by 25%, and low-sugar food prepared by boiling could also reduce the production of AGEs [152].”
Reference 152 is a review article: Cao C, Xiao Z, Wu Y, et al. Diet and Skin Aging-From the Perspective of Food Nutrition. Nutrients. 2020;12:870. Sentence: “However, strict control of blood sugar for four months can reduce the production of glycosylated collagen by 25%, and low-sugar food prepared by boiling can also reduce the production of AGEs [93–95].”
Reference 93 is a review article: Nguyen HP, Katta R. Sugar sag: Glycation and the role of diet in aging skin. Skin Ther Lett. 2015; 20: 1–5. Sentence: “Tight glycemic control over a 4-month period can result in a reduction of glycated collagen formation by 25%.37,38”
Reference 94 and 38 is a review article: Draelos ZD. Aging skin: the role of diet: facts and controversies. Clin Dermatol. 2013;31:701-6. Sentence: “Tighter glycemic control can reduce glycated collagen by 25% in 4 months.” No citation given.
Reference 95 and 37 is a review article: Danby FW. Nutrition and aging skin: Sugar and glycation. Clin. Dermatol. 2010;28: 409–11. Sentence: “...tight glycemic control can drop glycated collagen formation by 25% in 4 months.” No citation given.
MacMahon, B., Yen, S., Trichopoulos, D., Warren, K. and Nardi, G. Coffee and cancer of the pancreas. New England Journal of Medicine. 1981; 304: 630-633.
(04:57) - Actual dating profile wishlists vs study wishlists
(09:12) - Juicy paper details
(18:31) - What the study actually asked – wishlist, partner resume, relationship satisfaction
(24:10) - Linear regression illustrated through number of boats your partner has
(30:37) - Standardized regression coefficients illustrated through spouse height concordance
(34:52) - Good catch confounder: We all just want the same high-quality ice cream / mate
(39:46) - Does your personalized wishlist matter? Results
(42:01) - Wishlist regression interaction effects: like chocolate and peanut butter
(45:51) - Partner traits result in happiness bonus points
(49:51) - What do we say we want – and what really makes us happy? Surprise
(54:10) - Gender stereotypes and whether they held up
(56:51) - Random effects models and boats again
(59:30) - Other cool things they did
(01:00:41) - One-minute paper summary
(01:02:23) - Wrap-up, rate the claim, methodological morals
🇬🇧 Great Britain - science
11/09/2025
#14
🇬🇧 Great Britain - science
10/09/2025
#11
🇬🇧 Great Britain - science
09/09/2025
#4
🇬🇧 Great Britain - science
08/09/2025
#4
🇬🇧 Great Britain - science
07/09/2025
#9
🇬🇧 Great Britain - science
06/09/2025
#11
Spotify
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