Normal Curves: Sexy Science, Serious Statistics

Regina Nuzzo and Kristin Sainani
  • 4.9 (36)
  • Science
  • Updated Biweekly

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.

  1. Oct 19

    Researching Honesty: Can you trust the data? Part 1

    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. We follow the trail from a failed replication to some extraordinary detective work involving an Excel spreadsheet—and conduct a little statistical sleuthing of our own. Along the way, we discover how suspicious changes to a handful of observations can alter the story a scientific study tells. Statistical topics Statistical sleuthingData integrityData managementReplicationSensitivity analysisEffect sizesStatistical significanceReproducibilitySpreadsheetsConceptual replicationDirect replicationCalcChainMethodologic Morals “There's cleaning your data, and then there's laundering your data.” “Good data record keeping is still sexy. Version control, baby.” References References Published research Shu LL, Mazar N, Gino F, Ariely D, Bazerman MH. Signing at the beginning makes ethics salient and decreases dishonest self-reports in comparison to signing at the end. Proc Natl Acad Sci U S A. 2012;109(38):15197-15200. Retracted. doi:https://doi.org/10.1073/pnas.1209746109Kristal AS, Whillans AV, Bazerman MH, Gino F, Shu LL, Mazar N, Ariely D. Signing at the beginning versus at the end does not decrease dishonesty. Proc Natl Acad Sci U S A. 2020;117(13):7103-7107. doi:https://doi.org/10.1073/pnas.1911695117Retraction for Shu et al., Signing at the beginning makes ethics salient and decreases dishonest self-reports in comparison to signing at the end. Proc Natl Acad Sci U S A. 2021;118(38):e2115397118. doi:https://doi.org/10.1073/pnas.2115397118Data Colada investigations Simonsohn U, Simmons JP, Nelson LD. Evidence of fraud in an influential field experiment about dishonesty. Data Colada. August 17, 2021. https://datacolada.org/98Simonsohn U, Simmons JP, Nelson LD. Data falsificada (part 1): “Clusterfake.” Data Colada. June 17, 2023. https://datacolada.org/109Simonsohn U, Simmons JP, Nelson LD. Data falsificada (part 2): “My class year is Harvard.” Data Colada. June 20, 2023. https://datacolada.org/110Simonsohn U, Simmons JP, Nelson LD. Data falsificada (part 3): “The cheaters are out of order.” Data Colada. June 23, 2023. https://datacolada.org/111Simonsohn U, Simmons JP, Nelson LD. Data falsificada (part 4): “Forgetting the words.” Data Colada. June 30, 2023. https://datacolada.org/112Simonsohn U, Simmons JP, Nelson LD. Exhibits 3, 4, and 5. Data Colada. September 16, 2023. https://datacolada.org/114Simmons JP. Harvard's Gino report reveals how a dataset was altered. Data Colada. July 9, 2024. https://datacolada.org/118Additional resources Lessig L. The Gino Case. Website and podcast series presenting arguments challenging Harvard's research misconduct findings. https://theginocase.info/Gino v Harvard University. CourtListener. Federal court docket and publicly available filings. https://www.courtlistener.com/docket/67659904/gino-v-harvard-university/Simonsohn U, Simmons JP, Nelson LD. Data Falsificada. ResearchBox. Research data, analysis code, and supporting materials accompanying the Data Colada investigations. https://researchbox.org/1630.34Kristal AS, et al. Research materials and data accompanying Signing at the beginning versus at the end does not decrease dishonesty. Open Science Framework. https://osf.io/4b7mu/overviewCorrection for Kristal et al., Signing at the beginning versus at the end does not decrease dishonesty. Proc Natl Acad Sci U S A. 2026;123(27):e2610441123. doi:https://doi.org/10.1073/pnas.2610441123Harvard Business School. Investigative report concerning allegations of research misconduct involving Francesca Gino. Harvard Business School Research Integrity Investigation Report. 2023. Accessed October 18, 2026. https://datacolada.org/wp-content/uploads/Harvard-Report-on-Gino.pdfKristin and Regina’s online courses:  Demystifying Data: A Modern Approach to Statistical Understanding   Clinical Trials: Design, Strategy, and Analysis  Medical Statistics Certificate Program   Writing in the Sciences  Epidemiology and Clinical Research Graduate Certificate Program  Program that Kristin teaches in:: Epidemiology and Clinical Research Graduate Certificate Program  Kristin’s manuscript writing course: https://instats.org/seminar/from-data-to-discussion-writing-a-scient Find us on: Kristin -  LinkedIn & Twitter/X Regina - LinkedIn & ReginaNuzzo.com (00:00) - Cold Open: Two Frauds in a Paper About Honesty (02:41) - The Claim: Spreadsheets Are the Villain (05:43) - The 2012 Honesty Pledge Study (09:17) - Signing at the Top Wins (13:31) - Failed Replications: Five Conceptual Tries, Then...

    Researching Honesty: Can you trust the data? Part 1

  2. Oct 5

    Statistical Sleuthing: Can you spot a problem?

    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-detective hats and find a few statistical clues of our own before turning to Data Colada’s investigation of the original data, where the story gets even stranger. Along the way, we hunt for missing participants, question suspiciously enormous effects, meet some unlikely data twins, and discover why sometimes the best statistical tool is simply asking: Do these data behave like real people? Statistical topics Statistical sleuthingEffect sizesDegrees of freedomReplicationMissing dataMethodologic Morals “A data detective's toolbox is surprisingly simple. Check the degrees of freedom, look for twins, question giant effects, and ask whether the data actually make human sense.”“You don't have to be a statistician to catch a statistical criminal.” References Data Colada blog posts:https://datacolada.org/138https://datacolada.org/139Data and code: https://researchbox.org/7135Retraction Watch article: https://retractionwatch.com/2026/09/03/procrastination-study-duke-dan-ariely-psychological-science-data-colada-tampering-retraction/ Original 2002 paper: https://journals.sagepub.com/doi/10.1111/1467-9280.00441 Retraction notice: https://journals.sagepub.com/doi/10.1177/09567976261488042 Hyndman K, Bisin A. Replication of "Procrastination, Deadlines, and Performance: Self-Control by Precommitment". Psychol Sci. 2026;37(8):557-571. doi:10.1177/09567976261460772Kristin and Regina’s online courses:  Demystifying Data: A Modern Approach to Statistical Understanding   Clinical Trials: Design, Strategy, and Analysis  Medical Statistics Certificate Program   Writing in the Sciences  Epidemiology and Clinical Research Graduate Certificate Program  Program that Kristin teaches in:: Epidemiology and Clinical Research Graduate Certificate Program  Kristin’s manuscript writing course: https://instats.org/seminar/from-data-to-discussion-writing-a-scient Find us on: Kristin -  LinkedIn & Twitter/X Regina - LinkedIn & ReginaNuzzo.com (00:00) - Introduction (02:15) - The Procrastination Paper and Study Two (08:51) - Suspiciously Tidy Results (16:18) - Study One: Real Classroom Stakes (20:06) - Missing Data and First Red Flags (28:17) - How Data Colada Got the Data (33:43) - When the Replication Failed (35:36) - Red Flags: Data Twins and Sanity Checks (47:21) - Study One Gets the Spreadsheet Treatment (51:45) - The Grading Scheme Unravels (57:51) - Manuscript Versions Reveal the Truth (01:08:11) - Rating the Claim and Methodological Morals

    Statistical Sleuthing: Can you spot a problem?

  3. Sep 21

    Ctrl-Z Awards: Will retracting your paper ruin your career?

    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 suspicious spider data, three retracted papers, and the fear that going public might tank her career. Then computational social scientist Alyssa Smith tells us how one small error in a figure led her to retract the paper at the center of her PhD and job talk. Along the way, we talk about data forensics, the stigma around retractions, and why self-correcting scientists are the heart of science. Statistical topics Data management and documentationOpen scienceReproducible workflowsResearch integrityRetractionsScientific misconductStatistical forensics Methodologic Morals “Science is self-correcting, which means scientists need to be self-correcting too.”“Good documentation is boring—right up until it saves you.”“If you want scientists to correct their mistakes, reward them for correcting their mistakes.”“I'd rather be considered an honest idiot than for people to wonder if I'm untrustworthy.” References Retraction Watch: https://retractionwatch.com/Ctrl-Z Awards: https://retractionwatch.com/ctrl-z-award/Announcement of inaugural Ctrl-Z winners: https://centerforscientificintegrity.org/2026/08/04/2026-winners-ctrl-z-award-courage-retracting-own-work/ Kate Laskowski’s blog post: https://laskowskilab.faculty.ucdavis.edu/2020/01/29/retractions/Kate Laskowski’s Data Detective Course syllabusAlyssa Smith’s site: https://asmithh.github.io/ Laskowski KL, Montiglio PO, Pruitt JN. Individual and Group Performance Suffers from Social Niche Disruption [retracted in: Am Nat. 2020 Feb;195(2):393. doi: 10.1086/708066.]. Am Nat. 2016;187(6):776-785. doi:10.1086/686220Laskowski KL, Pruitt JN. Evidence of social niche construction: persistent and repeated social interactions generate stronger personalities in a social spider [retracted in: Proc Biol Sci. 2020 Jan 29;287(1919):20200077. doi: 10.1098/rspb.2020.0077.]. Proc Biol Sci. 2014;281(1783):20133166. Published 2014 Mar 26. doi:10.1098/rspb.2013.3166Modlmeier AP, Laskowski KL, DeMarco AE, et al. Persistent social interactions beget more pronounced personalities in a desert-dwelling social spider [retracted in: Biol Lett. 2020 Feb;16(2):20200062. doi: 10.1098/rsbl.2020.0062.]. Biol Lett. 2014;10(8):20140419. doi:10.1098/rsbl.2014.0419Smith AH, Green J, F Welles B, Lazer D. Emergent structures of attention on social media are driven by amplification and triad transitivity [retracted in: PNAS Nexus. 2026 May 07;5(5):pgag137. doi: 10.1093/pnasnexus/pgag137.]. PNAS Nexus. 2025;4(4):pgaf106. Published 2025 Apr 1. doi:10.1093/pnasnexus/pgaf106 Kristin and Regina’s online courses:  Demystifying Data: A Modern Approach to Statistical Understanding   Clinical Trials: Design, Strategy, and Analysis  Medical Statistics Certificate Program   Writing in the Sciences  Epidemiology and Clinical Research Graduate Certificate Program  Programs that we teach in: Epidemiology and Clinical Research Graduate Certificate Program  Find us on: Kristin -  LinkedIn & Twitter/X Regina - LinkedIn & ReginaNuzzo.com

    Ctrl-Z Awards: Will retracting your paper ruin your career?

  4. Sep 7

    Statistical Power: When is it useful?

    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 ethics of underpowered studies, and discover why post hoc power is really just a p-value wearing a fake mustache. Then statistician and powerlifter Andrew Althouse joins us for the inside story of a years-long scientific feud over post hoc power, where we discuss what happens when being wrong about statistics turns into doubling down, angry letters to the editor, and debates about how science corrects itself. Statistical topics Effect sizeFalse negativesP-valuesPost hoc powerPower calculationsResearch ethicsSample sizeScientific controversySensitivity analysisStatistical powerStatistical significanceStudy designType II error Methodologic Morals “Big questions need studies powerful enough to answer them.”“Post hoc power is circular reasoning masquerading as new information.”“Know when to cut your losses. A mistake gets more expensive every time you double down.”References Althouse AD, Chow ZR. Comment on “Post-hoc power: If you must, at least try to understand.” Ann Surg. 2019;270:e78-e79.Althouse AD. Post hoc power: Not empowering, just misleading. J Surg Res. 2021;259:A3-A6.Altman DG. Statistics and ethics in medical research: III. How large a sample? BMJ. 1980;281:1336-1338.Bababekov YJ, Hung YC, Hsu YT, et al. Is the power threshold of 0.8 applicable to surgical science?—empowering the underpowered study. J Surg Res. 2019;241:235-239.Bababekov YJ, Stapleton SM, Mueller JL, et al. A proposal to mitigate the consequences of type 2 error in surgical science. Ann Surg. 2018;267:621-622.Chang DC, Stapleton SM. Response: The proliferation and misinterpretation of “as safe as” statements in surgical science: A call for professional discourse to search for a solution. J Surg Res. 2021;259:A12-A15.Freiman JA, Chalmers TC, Smith H Jr, et al. The importance of beta, the type II error and sample size in the design and interpretation of the randomized control trial: Survey of 71 negative trials. N Engl J Med. 1978;299:690-694. Hoenig JM, Heisey DM. The abuse of power: The pervasive fallacy of power calculations for data analysis. Am Stat. 2001;55:19-24.Nuzzo RL. Statistical Power. PM&R. 2016;8(9):907-912. doi:10.1016/j.pmrj.2016.08.004Nuzzo RL. Post hoc Power. PM&R. 2021;13(4):422-424. doi:10.1002/pmrj.12476 Kristin and Regina’s online courses:  Demystifying Data: A Modern Approach to Statistical Understanding   Clinical Trials: Design, Strategy, and Analysis  Medical Statistics Certificate Program   Writing in the Sciences  Epidemiology and Clinical Research Graduate Certificate Program  Programs that we teach in: Epidemiology and Clinical Research Graduate Certificate Program  Find us on: Kristin -  LinkedIn & Twitter/X Regina - LinkedIn & ReginaNuzzo.com (00:00) - Intro (00:43) - What is Statistical Power? (03:22) - The UFO Telescope Analogy (06:19) - The Psychic Ability Experiment (10:36) - Planning Power Before You Study (12:46) - History and the Landmark 1978 Paper (17:42) - Enter Post-Hoc Power: The Problem (19:26) - Three Problems with Post-Hoc Power (24:33) - The Surgery Journal Disaster (29:59) - Guest Interview: Andrew Althouse (32:30) - The 2018 Paper and the Controversy Begins (39:54) - Doubling Down and the Cost of Being Right (53:03) - Rating the Claim

    Statistical Power: When is it useful?

  5. Aug 24

    Cannabis and Brain Aging: Can weed keep your brain young?

    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 testing, and how a press release subtly changed a story. We also meet permanently stoned mice, learn about Carl Sagan’s surprising connection to cannabis research, and discover how a single missing word can change the entire meaning of a study. Statistical topics Categorical variablesConfoundingEffect sizeFalse discovery rateHealthy volunteer biasMeasurement errorMultiple testingObservational studiesRecoding variablesScience communicationStatistical vs practical significance Methodologic Morals “Always follow the chain from data to result to conclusions and pay attention to the words along the way.”“Huge samples can give tiny differences delusions of grandeur.” References Guha A, Fu Z, Calhoun V, Hutchison KE. Lifetime Cannabis Use Is Associated With Brain Volume and Cognitive Function in Middle-Aged and Older Adults. J Stud Alcohol Drugs. 2026;87(4):739-751. doi:10.15288/jsad.25-00346Press Release: https://news.cuanschutz.edu/news-stories/study-finds-cannabis-usage-in-middle-aged-and-older-adults-associated-with-larger-brain-volume-better-cognitive-functionBilkei-Gorzo A, Albayram O, Draffehn A, et al. A chronic low dose of Δ9-tetrahydrocannabinol (THC) restores cognitive function in old mice. Nat Med. 2017;23(6):782-787. doi:10.1038/nm.4311NY Post: https://nypost.com/2026/02/07/health/cannabis-may-benefit-aging-brains-study-finds/David Grinspoon: https://www.nytimes.com/2020/07/02/science/lester-grinspoon-dead.html?unlocked_article_code=1.7lA.CyS1.neeqGGNgx8g1&smid=url-share Kristin and Regina’s online courses:  Demystifying Data: A Modern Approach to Statistical Understanding   Clinical Trials: Design, Strategy, and Analysis  Medical Statistics Certificate Program   Writing in the Sciences  Epidemiology and Clinical Research Graduate Certificate Program  Programs that we teach in: Epidemiology and Clinical Research Graduate Certificate Program  Find us on: Kristin -  LinkedIn & Twitter/X Regina - LinkedIn & ReginaNuzzo.com (00:00) - Opening: The Brain on Drugs (00:37) - The Cannabis Headline (03:38) - The Claim: Brain Benefits for Older Adults (06:53) - The Mouse Study: Pothead Mice vs. Control Mice (11:25) - From Mice to Humans: UK Biobank (15:01) - Measurement Problems and Category Collapse (21:39) - Results: Statistically Significant, Clinically Meaningless (27:13) - Individual Brain Regions and Cherry-Picking (32:32) - Cognitive Tests: What Actually Matters (40:09) - How It Gets Lost in Translation (45:32) - Rating the Claim

    Cannabis and Brain Aging: Can weed keep your brain young?

  6. Aug 10

    Double Duty: Can the meningitis vaccine also protect against gonorrhea?

    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 from per-protocol analysis, and why no amount of statistical adjustment can fully substitute for randomization. Along the way we celebrate outrageously named clinical trials, ask whether “flirting with statistical significance” belongs in a romance novel or a medical journal, and discover that “practice safe statistics” may be the best advice of the episode. Statistical topics Case-control studiesConfoundingEcological studiesGeneralizabilityIntention-to-treatMeta-analysisNull resultsObservational studiesP-valuesPer-protocol analysisRandomized clinical trialsSurvival analysis Methodologic Morals “Don't mistake a p-value of 0.06 for a p-value of 0.04 with bad luck.” “Practice safe statistics; randomize whenever possible.”References Seib KL, Donovan B, Jin F, et al. Meningococcal B Vaccine to Prevent Neisseria gonorrhoeae Infection. N Engl J Med. 2026; 395: 349-61.  Petousis-Harris H, Paynter J, Morgan J, et al. Effectiveness of a group B outer membrane vesicle meningococcal vaccine against gonorrhoea in New Zealand: a retrospective case-control study. The Lancet. 2017; 390: 1603–10. Wang, B., Mohammed, H., Andraweera, P., McMillan, M., Marshall, H., 2024. Vaccine effectiveness and impact of meningococcal vaccines against gonococcal infections: A systematic review and meta-analysis. Journal of Infection. 2024; 89: 106225.  Molina JM, Bercot B, Assoumou, L, et al. Doxycycline prophylaxis and meningococcal group B vaccine to prevent bacterial sexually transmitted infections in France (ANRS 174 DOXYVAC): a multicentre, open-label, randomised trial with a 2 × 2 factorial design. The Lancet Infectious Diseases. 2024; 24: 1093–1104. Thng C, Eskandari S, Jin F, et al. Efficacy of the meningococcal vaccine against Neisseria gonorrhoeae: a randomised clinical trial (MenGO). npj Vaccines. 2026. Still Not Significant | Probable Error: List of funny disguises scientists use to describe p>.05 Kristin and Regina’s online courses:  Demystifying Data: A Modern Approach to Statistical Understanding   Clinical Trials: Design, Strategy, and Analysis  Medical Statistics Certificate Program   Writing in the Sciences  Epidemiology and Clinical Research Graduate Certificate Program  Programs that we teach in: Epidemiology and Clinical Research Graduate Certificate Program  Find us on: Kristin -  LinkedIn & Twitter/X Regina - LinkedIn & ReginaNuzzo.com (00:15) - - Introduction (00:51) - - The Claim: Can a Meningitis Vaccine Prevent Gonorrhea? (04:10) - - The Biology Behind the Idea (10:37) - - How Observational Studies Made the Link (14:44) - - Earlier Clinical Trials: MENGO and DOXYVAC (17:30) - - Flirting with Significance: A Statistical Rant (22:40) - - GoGoVax: Study Design and Analysis (33:31) - - The Shocking Null Result (35:38) - - Why These Results Don't Generalize (37:42) - - Rating the Claim

    Double Duty: Can the meningitis vaccine also protect against gonorrhea?

  7. Jul 27

    Hot Tubbing: Can soaking in hot water help you run faster?

    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 physiological changes don’t necessarily translate into better athletic performance, and how an exploratory regression analysis ended up answering the wrong scientific question. We also discover that serious hot tub research involves surprisingly little relaxation, debate whether bubbles should count as an experimental condition, and learn why distance runners pay good money to sleep in tents with some of the oxygen sucked out. Statistical topics best subsets regressioncausal inferencecrossover studiesexploratory analysesmediation / mechanismsmodel specificationmultiple testingpeer reviewsample size (00:15) - Introduction (00:44) - Can Hot Tubs Replace Exercise? (01:27) - Crazy Runners and Crazy Training (05:44) - The Amazon Delivery System Metaphor (12:12) - From Heat Training to Hot Tubs (13:33) - The Study: 10 Runners in Hot Water (22:31) - Results and the VO2 Max Question (29:26) - Statistical Sleuthing: Best Subsets Regression (36:50) - The Peer Review Problem (41:39) - Rating the Claim Methodologic Morals “A model can be very good at answering the wrong question.” “The label ‘peer reviewed’ does not guarantee ‘carefully reviewed’.”References Jenkins EJ, Killick JA, Zerilli O, et al. Long-term passive heat acclimation enhances maximal oxygen consumption via haematological and cardiac adaptation in endurance runners. J Physiol. Published online November 20, 2025. doi:10.1113/JP289874Stembridge M, Jenkins E. Marathon training: Why hot baths might help you run faster. The Conversation. Published March 16, 2026. doi:10.64628/AB.6vknm9esh Kristin and Regina’s online courses:  Demystifying Data: A Modern Approach to Statistical Understanding   Clinical Trials: Design, Strategy, and Analysis  Medical Statistics Certificate Program   Writing in the Sciences  Epidemiology and Clinical Research Graduate Certificate Program  Programs that we teach in: Epidemiology and Clinical Research Graduate Certificate Program  Find us on: Kristin -  LinkedIn & Twitter/X Regina - LinkedIn & ReginaNuzzo.com (00:15) - Introduction (00:44) - Can Hot Tubs Replace Exercise? (01:27) - Crazy Runners and Crazy Training (05:44) - The Amazon Delivery System Metaphor (12:12) - From Heat Training to Hot Tubs (13:33) - The Study: 10 Runners in Hot Water (22:31) - Results and the VO2 Max Question (29:26) - Statistical Sleuthing: Best Subsets Regression (36:50) - The Peer Review Problem (41:39) - Rating the Claim

    Hot Tubbing: Can soaking in hot water help you run faster?

  8. Jul 13

    Exercise Snacks: Can just four minutes of exercise a day improve blood sugar?

    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 notes on our own exercise-snacking adventures, debate continuous glucose monitors, and ask how much evidence a single study should generate before it becomes health news. Statistical topics Crossover designMultiple testingPre-registrationPrimary vs secondary outcomesRandomized controlled trialResearch transparencyMethodologic Morals “It's good relationship advice to be transparent. It's also good research advice.”“If the primary outcome is not significant, say it up top.”References Babir FJ, Marcotte-Chénard A, Sandilands RE, et al. Exercise snacks performed in real-world settings reduce postprandial hyperglycaemia and glycaemic variability in individuals living with type 2 diabetes: a randomised crossover study. Diabetologia. 2026;69(8):2200-2211. doi:10.1007/s00125-026-06741-2https://www.washingtonpost.com/wellness/2026/05/28/4-minutes-exercise-day-could-help-control-blood-sugar/clinicaltrials.gov pre-registration with changes: https://clinicaltrials.gov/study/NCT06382246?term=NCT06382246&rank=1&tab=history&a=1&b=2#version-content-panel Kristin and Regina’s online courses:  Demystifying Data: A Modern Approach to Statistical Understanding   Clinical Trials: Design, Strategy, and Analysis  Medical Statistics Certificate Program   Writing in the Sciences  Epidemiology and Clinical Research Graduate Certificate Program  Programs that we teach in: Epidemiology and Clinical Research Graduate Certificate Program  Find us on: Kristin -  LinkedIn & Twitter/X Regina - LinkedIn & ReginaNuzzo.com (00:00) - Intro (04:06) - The claim: four minutes a day (07:05) - Our own N of 1 experiments (13:24) - The study (21:54) - Primary outcome: complete miss (25:16) - Secondary outcomes to the rescue? (35:02) - Statistical sleuthing and transparency (44:23) - Rating the claim

    Exercise Snacks: Can just four minutes of exercise a day improve blood sugar?
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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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