Are young people really having less sex? Headlines about a “sex recession” suggest a dramatic decline—but what do the data actually show? In this episode, we trace that claim back to the research behind it—and find a story that’s far more nuanced than the headlines suggest. We examine large national surveys, including the General Social Survey and the National Survey of Sexual Health and Behavior, and uncover how small analytical choices can completely change the story. Along the way, we tackle ordinal versus quantitative data, why averages can mislead, how logistic regression reframes the question, and what happens when researchers try to time-travel with statistics. Plus: the surprising role of extreme values, why “eight fewer sexual encounters per year” may not mean what you think, and whether young men and women are really following the same trends.
Statistical topics
Average vs distribution
Binary variables
Effect size vs statistical significance
Logistic regression
Measurement / operationalization
Ordinal variables
Outliers / extreme values
Self-reported datagoog
Social desirability bias
Variable coding / transformation
Methodological morals
“You shouldn't use data from people in their 80s to guess what they were doing in their 20s unless your data come with a time machine.”
“When extreme values drive the average, the average stops describing most people.”
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