Age Gaps: How much does age matter in dating?

Age Gaps: How much does age matter in dating?

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


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
  • (04:01) - Half-your-age-plus-seven rule
  • (09:15) - Matchmaking service for the study
  • (17:05) - Blind dates as natural experiments
  • (21:55) - Regression results part 1: Age penalties?
  • (28:38) - Wait, how big of an effect was that?
  • (34:09) - Odds ratio of a second date
  • (38:01) - Surprising age pair-ups
  • (40:53) - Regression results part 2: Deal-breaking age limits?
  • (44:27) - Why the patterns may or may not be true
  • (46:30) - Wrap-up, ratings, and methodological morals


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