Can exercise actually be bad for you if you don’t get enough sleep? A widely shared claim says yes—that working out while sleep deprived may speed up aging. In this episode, we put that claim under the microscope. We examine the study behind it, unpack how sleep and aging were measured, and explore key statistical ideas like interaction effects and flexible models that can “dance” to the data. With the help of a $400,000 handbag and a man with seven boats, we also break down what it really takes to show that one variable changes the effect of another. What we find: some clear study bloopers, inconsistent modeling results, and interpretations that are flat-out wrong.
Statistical topics
Measurement error
Model specification
Piecewise linear regression
Regression models
Residual confounding
Splines
Statistical interactions
Survey design
Methodological morals
“Before you believe something shocking, ask what had to go wrong to make it true.”
“If slight modeling changes flip the story, there wasn't much story to begin with.”
“Unethical Life Pro Tip: If you do not want your analysis critiqued, then just make it impossible to understand.”
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