The Beginner’s Guide to Quantified Self(technori.com) |
The Beginner’s Guide to Quantified Self(technori.com) |
I would be interested in analyzing the data after I had a large pool and a decent idea of shape, center, and spread, but I also don't trust myself to wait that long.
I'm not necessarily too worried about that. Statistical significance is the wrong concept for QS and its use is essentially cargo cult statistics.
Leaving aside the profound conceptual and applied problems with null-hypothesis testing ( http://lesswrong.com/lw/g13/against_nhst/ ), QS is much closer to cost-benefit analysis where effect sizes and costs are the critical variables, not alpha. We don't care about testing some intervention and not making the completely arbitrary cutoff of 0.05 (which doesn't mean anything about the truth of the hypothesis in the first place)! We care whether the intervention make a large impact on the variable in question and how expensive the intervention was; if, say, the intervention is an expensive supplement that costs hundreds of dollars a year, we want a higher burden of proof than if the intervention is something free (like taking your vitamin D supplement in the morning rather than evening) or something we should be doing anyway (like exercise).
Far* more worrisome than QS's failure to run t-tests and ritually chant 'we calculate a p-value of <0.05 therefore we reject the null hypothesis of no difference' is the pervasive publication bias (who reports failed experiments?), the absence of blinding even where quite easy leading to severe placebo effects (many supplements), tiny sample sizes, and dodgy data collection (selection bias).
* If you are wondering why anyone would care about my opinion, I've been self-experimenting for years and have a little bit of insight into the matter; see http://www.gwern.net/Zeo http://www.gwern.net/Nootropics and http://www.gwern.net/Weather
http://personalheartmonitor.com/sensors.html
I'd also have to recommend org-mode in Emacs, at least for time tracking. I know it's not "mobile", but I use it on my phone to track all sorts of things, and since the format is plain text, I can slice and dice in any language I want, no third parties needed.
On the subject of quantified self Stephen Wolfram's blog post 'The Personal Analytics of My Life' (http://blog.stephenwolfram.com/2012/03/the-personal-analytic...) is an interesting read.
They kept mentioning the "quantified self" and I didn't know what they were talking about.
But when I started tracking I found that while my overall weight wasn't changing, my percentage of body fat was dropping, indicating that I was in fact gaining muscle. It's not like this was technically new information, but seeing the numbers triggered some sort of response in me which made it very easy to keep going to the gym.
I also find it fun to start some runkeeper app when I go on bike rides, and that only takes about a minute or two before I start it. I never actually look at the history of my cardio workouts, but it's fun to have the stats while I'm biking, and to see a map of where I went after I'm done.
MyFitnessPal's UI is pretty bad but seems to have decent data if you can find it.
Fitbit's UI is nice but the food database and lookup is atrocious.
For any tracking that doesn't require support database (like food calories), I switched to TapLog [0]; it's the only sane tracking app I've seen so far. It allows you to place buttons on your homescreen to track custom-defined categories (I use, among others, Expense, Weight, Sleep time). You can store a number, a rate (1-5) OR a text description. And that's it. You press the button, type in the quantity, press "Log" and you're done. And it allows you to export all data to CSV - for me it's the most important feature (and without it, I won't be using any kind of tracking app).
[0] - https://play.google.com/store/apps/details?id=com.waterbear....
This is yet another area where people are attempting to layer technology on top of a problem that does not exist.
Why would you think that? If anything, the self quantified movement is all about thinking scientifically to improve yourself. Gathering data, analyzing, designing experiments, generating hypothesis, and publishing for feedback are all part of being self quantified.
The attitude that we can simply "optimize our life" is reductionist, arrogant, foolhardy. You will spend more time optimizing your numbers than you will living your life. But hey, at least you have the data to back it up :-)
But at the same time, we're surrounding ourselves with so many sensors that for the first time in the history of mankind we can really "data mine ourselves". This may bring up interesting discoveries.
In the early days of science some kept strict logs about everything they did with the same goal. Now this can be automated.
Sure no one is saying quantified will get you from a 1 to a 10 on the happiness scale, but it will definitely help you to learn more about yourself.
- I don't need to track my happiness to know if I'm happy.
- I don't need to track my sleeping patterns to learn how to sleep better.
- I don't need to track every calorie to know if I'm eating well.
- I don't need a computer to tell me if I'm healthy.
It seems to me that QS is just a new fad that will make a certain personality type feel like they have control over their lives."Quantified Self -- Using numbers, technology, and science to divine common sense!"
EDIT: bleh, and now that I look at my original comment, I see I failed to escape an asterisk so the formatting is completely screwed up.