Comment by gjulianm
1 day ago
> Effect survives controlling for activity level.
How did you control for activity level? Do you have similar BPM plots for the different situations (sauna+exercise, sauna+no exercise, no sauna + exercise, no sauna + no exercise) for a visual representation?
> minimum nighttime HR drops ~3 bpm (~5%)
What wearables were used? These devices don't usually have enough precision to reliably detect ~3bpm changes. Also, the measurements are sensitive to skin, blood flow changes and temperature. How do you know the difference doesn't come from different sensor behavior after sauna?
> What wearables were used? These devices don't usually have enough precision to reliably detect ~3bpm changes.
For large sample averages this doesn't really matter.
It does, specially if the error bars from multiple measurements show higher precision than what would be expected.
I don't understand what you mean by that.
Precision (inverse of variance) of estimate of mean increases directly proportional to number of samples (given some assumptions that very likely hold here). If you have measurement standard deviation of say 10 bpm, with 100 measurements you have mean estimate standard deviation of 10/sqrt(100) = 1 bpm.
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