1. The Curse of Big Data in Mobile Analytics Dr. Guodong (Gordon) Gao M-CERSI Workshop, 9/11/2015

2. Mobile devices = Big Data  User generated data  Facebook ingests 500 terabytes of new data every day.  Text messages, diet log, photos, videos, …  System generated data  App download and usage  Gesture, touches  Communications with other wearable devices  Sensor-generated data  6 billion mobile phones  Geo-location data, pedometer, heart beat sensor, and oxygen saturation sensor 2

3. Even more data 3

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7. Causal inference  Most the statistical methods try to measure correlations, not causation.  For actionable knowledge, we need causation!  Does the roster crowing cause the sun to rise?  Confusing correlation with causality can be dangerous 7

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10.  Does Anne Hathaway help Warren Buffet get richer? 10

11. The curse of big data  Heterogeneity in Treatment Effects (HTE)  Sub-group analysis  Helps answer:  Which sub-group will benefit from this treatment?  Should I prescribe the treatment to this particular patient?  With dozens of variable, and thousands of combinations, we can define sub-group in many ways  e.g. 10 variables, each with 3 levels, there are 3^10 = 59,049 combinations!  We are doomed to find something statistically significant in certain sub-groups 11

12. Yet another curse of big data 12

13. Do not ignore the fundamentals  Patient #11 13