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Normal Curves: Sexy Science, Serious Statistics

Regina Nuzzo and Kristin Sainani
Normal Curves: Sexy Science, Serious Statistics
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  • Dating Wishlists: Are we happier when we get what we want in a mate?
    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 topicsRegressionRandom Slopes and Intercepts (Random Effects) in RegressionStandardized Beta Coefficients in RegressionInteraction Effects in RegressionMean CenteringExploratory AnalysesMethodological 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.”ReferencesEastwick 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. A worldwide test of the predictive validity of ideal partner preference matching. J Pers Soc Psychol. 2025 Jan;128(1):123-146. doi: 10.1037/pspp0000524Love Factually Podcast: https://www.lovefactuallypod.com/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/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - (00:00) - Intro (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
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  • Stats Reunion: What have we learned so far?
    It’s our first stats reunion! In this special review episode, we revisit favorite concepts from past episodes—p-values, multiple testing, regression adjustment—and give them fresh personalities as characters. Meet the seductive false positive, the clingy post hoc ex, and Charlotte, the well-meaning but overfitting idealist.Statistical topicsBar charts vs Box plotsBonferroni correctionConfoundingFalse positives Multiple testingMultivariable regressionOutcome switchingOver-adjustmentPost hoc analysisPre-registrationResidual confoundingStatistical adjustment using regressionSubgroup analysis Unmeasured confoundingReview SheetReferencesNuzzo RL. The Box Plots Alternative for Visualizing Quantitative Data. PM R. 2016 Mar;8(3):268-72. doi: 10.1016/j.pmrj.2016.02.001. Epub 2016 Feb 15. PMID: 26892802.Sainani KL. The problem of multiple testing. PM R. 2009 Dec;1(12):1098-103. doi: 10.1016/j.pmrj.2009.10.004. PMID: 20006317.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/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - Intro (02:26) - Mailbag (06:42) - P-values (12:43) - Multiple Testing Guy (16:05) - Bonferroni solution (17:11) - Post hoc analysis ex (22:22) - Subgroup analysis person (29:34) - Statistical adjustment idealist (43:00) - Unmeasured confounding (44:25) - Residual confounding (48:31) - Over-adjustment (53:48) - Wrap-up
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  • HPV Vaccine: How close are we to wiping out cervical cancer?
    Could a preteen vaccine wipe out a global cancer? In this episode, we examine the bold claim that cervical cancer could be eradicated in much of the world by the end of the century—thanks to the highly effective HPV vaccine. We unpack statistical modeling, microsimulations, and how Markov chains make good date-night conversation. We also explore why vaccine uptake has been uneven, how a splash of vinegar is helping screen for cancer in low-resource countries, and why HPV isn’t just a women’s issue—it now causes more cancer in men than in women. Plus: dangerously tight corsets, allegedly breast-squeezing nuns, and the Cosmo quote we wish we’d written ourselves.Statistical topics:Cancer surveillanceMarkov modelsMicrosimulation modelsSensitivity analysesPassive surveillanceBackground ratesCase reports and case seriesMethodologic morals:“When reality is too complex to test, let microsimulations do the rest.”“Case reports are medicine's equivalent to see something, say something. They call for hard data, not hysteria.”Citations:No cervical cancer cases detected in vaccinated women following HPV immunisation. University of Strathclyde, January 22, 2024.Palmer TJ, Kavanagh K, Cuschieri K, et al. Invasive cervical cancer incidence following bivalent human papillomavirus vaccination: a population-based observational study of age at immunization, dose, and deprivation. J Natl Cancer Inst. 2024;116:857-65.Rigoni-Stern. Statistical facts about cancers on which Doctor Rigoni-Stern based his contribution to the Surgeons' Subgroup of the IV Congress of the Italian Scientists on 23 September 1842. (translation). Stat Med. 1987;6:881-4.Gordan JA, Lenkei SC. Cleanliness, Continence, Constancy, and Cervical Carcinoma. Can Med Assoc J. 1964;90:1132.zur Hausen H. Condylomata acuminata and human genital cancer. Cancer Res. 1976;36:794.Walboomers JM, Jacobs MV, Manos MM, et al. Human papillomavirus is a necessary cause of invasive cervical cancer worldwide. J Pathol. 1999;189:12-9.Chesson HW, Dunne EF, Hariri S, et al. The estimated lifetime probability of acquiring human papillomavirus in the United States. Sex Transm Dis. 2014;41:660-4.Sullivan, Morgan. Let’s Have a Little Chat About the HPV Vaccine. Cosmopolitan. March 19, 2025.Burger EA, Kim JJ, Sy S, et al. Age of Acquiring Causal Human Papillomavirus (HPV) Infections: Leveraging Simulation Models to Explore the Natural History of HPV-induced Cervical Cancer. Clin Infect Dis. 2017;65:893-99.Canfell K. Towards the global elimination of cervical cancer. Papillomavirus Res. 2019;8:100170.World Health Organization. Global strategy to accelerate the elimination of cervical cancer as a public health problem. November 17, 2020.Hall MT, Simms KT, Lew JB, et al. The projected timeframe until cervical cancer elimination in Australia: a modelling study. Lancet Public Health. 2019;4:e19-e27.Burger EA, Smith MA, Killen J, et al. Projected time to elimination of cervical cancer in the USA: a comparative modelling study. Lancet Public Health. 2020 Apr;5(4):e213-e222.Brisson M, Kim JJ, Canfell K, et al. Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries. Lancet. 2020;395:575-90.Escabí-Wojna E, Alvelo-Fernández PM, Suárez E, et al. Sex differences in parental reasons for lack of intent to initiate HPV vaccination among adolescents ages 13-17 years: National Immunization Survey - Teen 2019-2021. Vaccine. 2025;44:126584. (see supplement) Szilagyi PG, Albertin CS, Gurfinkel D, et al. Prevalence and characteristics of HPV vaccine hesitancy among parents of adolescents across the US. Vaccine. 2020;38:6027-6037.LaPook, Jonathan. Is the HPV Vaccine Safe? CBS Evening News. August 18, 2009.Slade BA, Leidel L, Vellozzi C, et al. Postlicensure safety surveillance for quadrivalent human papillomavirus recombinant vaccine. JAMA. 2009;302:750-7.Kharabsheh S, Al-Otoum H, Clements J, et al. Mass psychogenic illness following tetanus-diphtheria toxoid vaccination in Jordan. Bull World Health Organ. 2001;79:764-70.Jones TF, Craig AS, Hoy D, et al. Mass psychogenic illness attributed to toxic exposure at a high school. N Engl J Med. 2000;342:96-100.Buttery JP, Madin S, Crawford NW, et al. Mass psychogenic response to human papillomavirus vaccination. Med J Aust. 2008;189:261-2.Clements CJ. Gardasil and mass psychogenic illness. Aust N Z J Public Health. 2007;31:387.Simas C, Munoz N, Arregoces L, et al. HPV vaccine confidence and cases of mass psychogenic illness following immunization in Carmen de Bolivar, Colombia. Hum Vaccin Immunother. 2019;15:163-66.Larson HJ. Japan's HPV vaccine crisis: act now to avert cervical cancer cases and deaths. Lancet Public Health. 2020;5:e184-e185.Brinth LS, Pors K, Theibel AC, Mehlsen J. Orthostatic intolerance and postural tachycardia syndrome as suspected adverse effects of vaccination against human papilloma virus. Vaccine. 2015;33:2602-5.Large well-done studies following up on case reports and passive surveillance:Phillips A, Hickie M, Totterdell J, Brotherton J, Dey A, Hill R, Snelling T, Macartney K. Adverse events following HPV vaccination: 11 years of surveillance in Australia. Vaccine. 2020;38:6038-46.Arnheim-Dahlström L, Pasternak B, Svanström H, et al.
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  • Equipment Size: What is average?
    Today’s deep dive: the surprisingly serious science of penis size. Using self-report surveys, objective measurements, and a healthy dose of old-school statistics, we ask: How do you get clean data on gentlemen’s goods?Along the way, we explore social desirability bias, survey design tricks, and what happens when science meets insecurity. You’ll never look at a Starbucks cup the same way again.Statistical topicsSocial desirability biasSelection biasVolunteer BiasDescriptive StatisticsRight-Skewed DistributionsStrategies to improve accuracy in self-report dataMethodological morals“When answers aim to please, truth takes its leave.”“Without descriptive statistics, you'll never know if you measure up.”ReferencesCROWNE DP, MARLOWE D. A new scale of social desirability independent of psychopathology. J Consult Psychol. 1960;24:349-354. doi:10.1037/h0047358Gebhard, P.H. and Johnson, A.B., 1998. The Kinsey data: Marginal tabulations of the 1938-1963 interviews conducted by the Institute for Sex Research. Indiana University Press.Herbenick D, Reece M, Schick V, Sanders SA. Erect penile length and circumference dimensions of 1,661 sexually active men in the United States. J Sex Med. 2014;11(1):93-101. doi:10.1111/jsm.12244Johnston, L., McLellan, T., & McKinlay, A. (2014). (Perceived) size really does matter: Male dissatisfaction with penis size. Psychology of Men & Masculinity, 15(2), 225–228. https://doi.org/10.1037/a0033264King BM. The Influence of Social Desirability on Sexual Behavior Surveys: A Review. Arch Sex Behav. 2022;51(3):1495-1501. doi:10.1007/s10508-021-02197-0King BM. Average-Size Erect Penis: Fiction, Fact, and the Need for Counseling. J Sex Marital Ther. 2021;47(1):80-89. doi:10.1080/0092623X.2020.1787279King BM, Duncan LM, Clinkenbeard KM, Rutland MB, Ryan KM. Social Desirability and Young Men's Self-Reports of Penis Size. J Sex Marital Ther. 2019;45(5):452-455. doi:10.1080/0092623X.2018.1533905Larson, R.B., 2019. Controlling social desirability bias. International Journal of Market Research, 61(5), pp.534-547.Stodel, M. (2015). But What Will People Think?: Getting beyond Social Desirability Bias by Increasing Cognitive Load. International Journal of Market Research, 57(2), 313-322. https://doi.org/10.2501/IJMR-2015-024   (Original work published 2015)Spreadsheet with Penis Length DataOur online courses and programs: 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 Find us on social:Kristin -  LinkedIn & Twitter/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - Introduction (02:33) - Starbucks metric and episode themes (07:17) - Men and women’s sampling frames (09:24) - Kinsey and his studies (14:59) - Statistics quiz on Kinsey penis data (21:16) - Social desirability bias (28:23) - Cognitive tricks to elicit honest survey answers (34:16) - Condoms, honest penis lengths, and another stats quiz (40:36) - Objective penis appraisers, measurement error, and reliability (45:48) - Whose penises? Volunteer and selection bias (49:33) - Mini-meta-analysis and the “answer” (51:12) - Wrap-up and methodological morals
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  • Sugar Sag: Is Your Diet Aging You?
    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 setsStatistical adjustmentOverfitting PlagiarismProper citing practicesReferences to nowhereMethodologic 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.”CitationsCollagen turnover: Verzijl N, DeGroot J, Thorpe SR, et al.Effect of Collagen Turnover on the Accumulation of Advanced Glycation End Products. JBC. 2000;275:39027-31.Cadaver study:Hamlin CR, Kohn RR, Luschin JH. Apparent Accelerated Aging of Human Collagen in Diabetes Mellitus. Diabetes. 1975; 24: 902–904.AGE ReaderStudies of AGEs and diabetes and health:Monnier VM, Cerami A. Nonenzymatic browning in vivo: possible process for aging of long-lived proteins. Science. 1981;211:491-3. Brownlee M, Vlassara H, Cerami A. Nonenzymatic glycosylation and the pathogenesis of diabetic complications. Ann Intern Med. 1984;101:527-37. Monnier VM, Vishwanath V, Frank KE, et al. Relation between Complications of Type I Diabetes Mellitus and Collagen-Linked Fluorescence. N Engl J Med. 1986;314:403-408.Monnier VM, Sell DR, Abdul-Karim FW, et al. Collagen browning and cross-linking are increased in chronic experimental hyperglycemia. Relevance to diabetes and aging. Diabetes. 1988;37:867-72. Monnier VM, Bautista O, Kenny D, et al. Skin collagen glycation, glycoxidation, and crosslinking are lower in subjects with long-term intensive versus conventional therapy of type 1 diabetes: relevance of glycated collagen products versus HbA1c as markers of diabetic complications. Diabetes 1999; 48: 870–80.Genuth S, Sun W, Cleary P, et al. Glycation and carboxymethyllysine levels in skin collagen predict the risk of future 10-year progression of diabetic retinopathy and nephropathy in the diabetes control and complications trial and epidemiology of diabetes interventions and complications participants with type 1 diabetes. Diabetes. 2005;54:3103-11. van Waateringe RP, Slagter SN, van Beek AP, et al. Skin autofluorescence, a non-invasive biomarker for advanced glycation end products, is associated with the metabolic syndrome and its individual components. Diabetol Metab Syndr. 2017;9:42. Kouidrat Y, Zaitouni A, Amad A, et al. Skin autofluorescence (a marker for advanced glycation end products) and erectile dysfunction in diabetes. J Diabetes Complications. 2017;3:108-113. Fujita N, Ishida M, Iwane T, et al. Association between Advanced Glycation End-Products, Carotenoids, and Severe Erectile Dysfunction. World J Mens Health. 2023;41:701-11. Uruska A, Gandecka A, Araszkiewicz A, et al. Accumulation of advanced glycation end products in the skin is accelerated in relation to insulin resistance in people with Type 1 diabetes mellitus. Diabet Med. 2019;36:620-625. Boersma HE, Smit AJ, Paterson AD, et al. Skin autofluorescence and cause-specific mortality in a population-based cohort. Sci Rep 2024;14:19967.Review article with conflicts of interest: Draelos ZD. Sugar Sag: What Is Skin Glycation and How Do You Combat It? J Drugs Dermatol. 2024; 23:s5-10.Clinical study on AGE interrupter cream:Draelos ZD, Yatskayer M, Raab S, Oresajo C. An evaluation of the effect of a topical product containing C-xyloside and blueberry extract on the appearance of type II diabetic skin. J Cosmet Dermatol. 2009;8:147-51. The citation trail: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.The origi...
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About Normal Curves: Sexy Science, Serious Statistics

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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