Note: This is a WIP; I’ll build on this post from time to time when I make changes to the method, calculate new statistics or gain other new insights.
I’ve never really thought that the Quantified self movement was the right fit for me. There are certain things I’ve tried before, though. For example, I’ve tracked my calories rather successfully but only over a relatively short amount of time, and just in order to get a better feeling for my nutrition and wing it from there. But tracking stuff over a longer period of time? No thanks, I’m fine trying to keep my TODOs from taking over my life already…
However, I do, in general, try to optimize my life. I plan quite a bit in order to feel and be more fit, alert and productive: I try to sleep for eight hours in order to be alert the next day, I build habits that I know will benefit me, I try to eat healthily and exercise regularly because it makes me feel great. But how can I be so sure that eight hours is the right amount of sleep for me, or that my habits are actually sensible?
Today, I figured that it actually doesn’t have to be that much work to find out.
I will start a data diary which let’s me check on various correlations in my life, like How does the amount of sleep I get correlate with how productive I feel?, How do the people I spend my time with correlate with how happy I feel? or Is meditation correlated with my perceived stress levels?
I already journal every day to get a detailed insight into my life and reflect on things, but I believe a more data-driven approach will be a fun and effective addition. I know it’s a pretty coarse method, but I bet I can get some valuable insights out of this what, daily 1 minute investment?
At first, I will need some data, so today I set up a Google sheets table, currently containing the following fields (I might add/remove fields eventually, as I see fit):
I use Google sheets because – like any other spreadsheet program – it lets me calculate certain fields automatically, e.g. hours of sleep, and is easy to access. I plan to convert this sheet to a CSV file at a later time and launch some heavy statistics on it, but more on that once the data has thoroughly thrived. There’s not too much one could (or should) infer from a single sample.
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