Episode
Age Gaps: How much does age matter in dating?
- Published
- Aug 25, 2025
- Duration seconds
- 2982
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Summary
Are we all secretly ageist when it comes to dating? We put the stereotype that older men prefer younger women under the microscope using data from thousands of blind dates. What we found surprised us: the “age penalty” was real but microscopic, women wanted younger partners too, and hard age cutoffs weren’t so hard after all. Along the way, we unpack statistical significance versus practical importance, play with the infamous “half your age plus seven” rule, and imagine what it would take for love to die out… somewhere around age 628. Statistical topics Discontinuous regression Effect sizes Extrapolation pitfalls Linear regression Logistic regression Odds ratios Open data Statistical significance vs. practical significance Methodological morals “ Do not be swept off your feet by statistical significance. Tiny effects in bed are still tiny. ” “ Fancy units sound smart, but plain English wins hearts .” Show Notes Technical Appendix (with step-by-step explanations) References Eastwick PW, Finkel EJ, Meza EM, Ammerman K. No gender differences in attraction to young partners: A study of 4500 blind dates. Proc Natl Acad Sci U S A. 2025 Feb 4;122(5):e2416984122. Matchmaking Dataset and Code on Open Science Framework: https://osf.io/rkm2d/?view_only=a0fe91dae0464077af7772e6890a8151 Nuzzo RL. Communicating measures of relative risk in plain English . PM&R. 2022 Feb;14(2):283-7. O'Rell, Max. Her Royal Highness, Woman: And His Majesty--Cupid . Abbey Press, 1901. Sainani KL. Logistic regression . PM&R. 2014 Dec;6(12):1157-62. Sainani KL. Understanding odds ratios . PM&R. 2011 Mar;3:263-7. Sainani KL. Clinical versus statistical significance . PM&R. 2012 Jun;4:442-5. Kristin and Regina’s online courses: Demystifying Data: A Modern Approach to Statistical Understandi…