Other director: "Hey Levi, we're having a meeting on the online project and would like your opinion could you join us for a few minutes?"
Me: "Um, well.. I'm eating cheese fries right now... can you hold.. ah hell, can I bring the cheese fries with me?"
Other director: "I guess...."
I mainly run/be active because of my massive food habit. But for my activity level I would weigh 300 lbs. So, I need to nerdily track my activity level, at least for the near future. I promise I won't post every week on this.
First the good news from this week:
- I averaged 3,000 more steps than last week.
- I slept, on average, 20 minutes fewer each night. I didn't feel tired though, so I think this metric may be more about consistency (low variance) than about mean sleep hours.
Now back to the nerdy part. I only have 18 data points, so I really shouldn't be modelling this data. But I will anyways, because I'm excited about it, and it's what I do.
Anyways, down the road I want to build out a fuller, multi-factor model, but for now I wanted to look at two factors: prior night sleep and "weekend." Here's what I learned:
- Prior night sleep: positively correlated, meaning the more I sleep, the more I move the next day, though not enough data for statistical significance, and the realized impact is only 500 additional steps per incremental hour of sleep.
- Weekend: I move a lot more on weekend days. Statistically significant. I end up moving almost 5700 steps more on the weekend than on normal weekdays.
So, this is my first post with any kind of fit tracker data analysis. I'm closing in on my 20,000 step per day average, which will be good to have. The initial results aren't surprising, but I'm still hoping to derive a counter-cyclical workout schedule from future data.
Model specification with parameter estimates.
Plot of hours slept versus steps, showing positive correlation.