Quantified Self Adventures at Wolfram

My adventures analyzing personal data at Wolfram, as lead data analyst on the March 2012 quantified self blog post.

April 2014, Data Raves NYC: http://www.meetup.com/Data-Rave/events/170730922/

Transcript

1. Slide 1 of 17
   Quantified Self Adventures at Wolfram
   Paul-Jean Letourneau
   Hacker School W’
   14
   0 100 200 300 400
   interval ms
   w o o l l f f r r a a m
   

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2. Stephen Wolfram’
   s blog post (March 2012)
   I was the lead data analyst for Stephen Wolfram’
   s quantified self blog post:
   2 data-rave-slides.nb
   

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3. email
   We had about 20 years worth of personal data!
   Each dot is a sent email on date X and time Y (“
   diurnal plot”
   ):
   data-rave-slides.nb 3
   

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4. keystrokes
   The diurnal plot of keystrokes is very similar to the email plot:
   4 data-rave-slides.nb
   

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5. phone calls and meetings
   Phone call spikes on the hour? Why?
   Because that’
   s when his meetings are (he’
   s remote so all his meetings are on the phone):
   (The ‘
   tails’
   on the phone peaks show he’
   s often late to his meetings.)
   data-rave-slides.nb 5
   

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6. Awesome! Show me the code!
   6 data-rave-slides.nb
   

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7. follow-up blog posts
   We wrote several follow-up posts showing detailed code for analyzing email, keystrokes, and pedometer data:
   data-rave-slides.nb 7
   

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8. I wrote an interface for analyzing your keystrokes:
   8 data-rave-slides.nb
   

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9. data collection
   Type “
   wolfram” a bunch of times, then grab the data:
   data-rave-slides.nb 9
   

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10. my keystrokes
    Letter pair intervals when typing “
    wolfram” (after 50 trials):
    intervals Transpose Differences keydata All, All, 2 ;
    Labeled
    ListLinePlot intervals,
    Mesh All, PlotStyle colors, PlotLegends SwatchLegend colors, nicelabel pchars , ImageSize 500
    , nicelabel "letter interval sec " , nicelabel "trial" , Left, Bottom , RotateLabel True
    letter interval sec
    10 20 30 40 50
    0.04
    0.06
    0.08
    0.10
    0.12
    0.14
    0.16
    0.18
    w o
    o l
    l f
    f r
    r a
    a m
    trial
    10 data-rave-slides.nb
    

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11. letter interval distribution
    My letter pair interval distribution is bimodal:
    Labeled keyhistogram intervals, ChartStyle colors, ImageSize 600,
    AspectRatio 1 2, PlotLabel nicelabel "Letter interval distribution Paul Jean " ,
    nicelabel "interval ms " , SwatchLegend colors, nicelabel pchars , Bottom, Right , Spacings Automatic, 0
    50 100 150
    10
    20
    30
    Letter interval distribution Paul Jean
    w o
    o l
    l f
    f r
    r a
    a m
    interval ms
    data-rave-slides.nb 11
    

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12. the “
    same finger” rule?
    Letter pairs on the same finger ~ 150 ms
    Letter pairs on different fingers ~ 75 ms
    Mean Flatten intervals 1, 3, 5, 6
    0.074238
    Mean Flatten intervals 2, 4
    0.144710
    Does it take about twice as long for other people too?
    12 data-rave-slides.nb
    

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13. company experiment
    I got keystroke data from 42 data nerds at Wolfram:
    meanswolfram Mean Transpose Differences & All, All, 2 & wolframdata;
    Legended
    Grid Partition keychart , ImageSize 100, ChartStyle Directive Opacity 0.6 , & colors & meanswolfram,
    7, 7, 1, , SwatchLegend colors, nicelabel pchars
    w o
    o l
    l f
    f r
    r a
    a m
    data-rave-slides.nb 13
    

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14. Wolfram nerds typing “
    wolfram”
    The Wolfram interval distribution was bimodal too, also with peaks at about 75 ms and 150 ms:
    intervalswolfram Flatten Transpose Transpose Differences All, All, 2 & wolframdata ;
    0 100 200
    w o
    o l
    l f
    f r
    r a
    a m
    interval ms
    14 data-rave-slides.nb
    

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15. linear model
    ... But it’
    s not just a 2x rule (the best linear model has a bias):
    twofingers Transpose Differences All, All, 2 1, 3, 5, 6 & wolframdata;
    onefinger Transpose Differences All, All, 2 2, 4 & wolframdata;
    fingersFit LinearModelFit Transpose Mean Flatten & twofingers, Mean Flatten & onefinger , x, x
    FittedModel
    0.106044 0.490341 x
    Letter intervals for Wolfram nerds in ms
    same finger
    50 100 150 200 250
    50
    100
    150
    200
    250
    300
    different fingers
    data-rave-slides.nb 15
    

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16. conclusions
    Stephen Wolfram’
    s quantified self blog made a splash.
    But people said: show me the code!
    Our follow-up posts showed people how to analyze their own data.
    Fun modeling keystrokes times with Mathematica.
    16 data-rave-slides.nb
    

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17. thanks!
    @rule146
    data-rave-slides.nb 17
    

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