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Sydney Self-knowledge through numbers

Sydney Self-knowledge through numbers. Significant Outliers. How much can one data point inform ? By Bo Li. The default method. The scientific method most of us will be familiar with. Aims to maximize accuracy Make informed hypothesis Design experiment to test

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Sydney Self-knowledge through numbers

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  1. Sydney Self-knowledge through numbers

  2. Significant Outliers How much can one data point inform? By Bo Li

  3. The default method • The scientific method most of us will be familiar with. • Aims to maximize accuracy • Make informed hypothesis • Design experiment to test • Analyse and adjust if necessary

  4. Peripheral Observation • Novel experiences besides those intended to be measured. • Concordant • Weight loss • Less mental fog • Discordant • Improved productivity • Feeling sleepy earlier • Jaw tension

  5. Relevant xkcd

  6. Enter Outliers • An observation that lies outside normal experience. • Generally inadequately accounted for by conventional measures of significance. • ‘One perfect day’ • ‘Turkey problem’

  7. Convergence of coincidences • A single outlier generally only indicates ‘weak’ associations. • Prone to false positives but useful as starting point. • Zero frequency • Convergent events

  8. Ex1: Stomach cramps • Hereditary condition causing painful cramps and gastrointestinal upset. • Irregular av.~1/month in frequency • Last experienced 04/03/12 Unknown 2012

  9. Ex2: Emwave • Device measuring HRV. • Subjective feeling of being ‘calmer’ and more present. • Two outliers: felt fine, but could not get device to turn green. • Next day spent fixing/scraping code due to glaring errors.

  10. Ex3: Mystery rash • May-12 development of a bad rash in the small of the back. • Tried balm, extra padding, change chair, etc • Rash went away. • Jun-13 Shortly after moving workstations, had relapse. • Change of chair as common element.

  11. Method summary • Track events outside normal experience and recurrent, unusual events. • Conduct self-experiments as normal. • Build associations between experiments and observations. • Strength of association determined by degree of changed experience.

  12. Benefits and Drawbacks • Very little effort spent to log. • Does not require a priori hypothesis. • Less time needed for results. • Ability to find meaning in fairly trivial or transient events. • Visceral rather than abstract associations. • Misses slight incremental improvements. • Lacks rigour

  13. Questions?

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