I’ve been tracking my sleep data for months with my wearable, and I’ve noticed something odd—my deep sleep phases seem to cluster around nights when I’ve done moderate exercise in the morning, but the correlation isn’t perfect. I’m trying to figure out if this is a real pattern or just random noise, and I’m not sure how to properly isolate the variables or what kind of statistical approach would even make sense here for a personal dataset.
One approach is to treat this like a tiny observational study and compare deep sleep minutes on nights after morning moderate exercise with nights after no exercise, using a simple paired comparison across your data set.
Wearable deep sleep measurements can be noisy and different devices use different baselines so the signal might be weak even if there is a real effect.
Maybe the pattern is more about how well you slept overall and how alert you feel the next day rather than a direct cause effect from exercise.
I would feel excited if I saw a real link but also cautious because life events like caffeine or stress can skew things What else should I track to be sure?
If you are assuming deep sleep increases with a jog in the morning you might be attributing to exercise a role that the data does not prove yet and you could be mistaking short term wake ups for rest cycles.
Think about how you frame the question for yourself and what you expect to see. Sometimes the story you tell about the data shapes what you notice.
A stronger stance would be to test if the effect persists after removing confounds like total sleep time and bedtime consistency and to think in terms of effect size rather than strict significance