11 Oct 2017

Data Science Philippines: Causal Inference and Big Data

This talk provides a high-level, fairly non-technical introduction to causal discovery using big data; i.e., how to carefully draw causal conclusions from big data analyses. Two general, complementary approaches for causal discovery will briefly be illustrated in the context of big data analysis: 1.) mechanism-focused and structural approaches using causal graphs, and 2.) the effect-focused statistical framework of potential outcomes (emphasis on the latter).

15 Mar 2017

Three Statistically Significant Principles

This is a short presentation I gave at the Quantified Self Bay Area Meetup event titled "Show & Tell #41" on March 15, 2017.  Summary:

  1. Big data does not imply big accuracy. (S)

  2. Significance does not imply importance. (S)

  3. Correlation does not imply causation. (P)

  4. Causation can imply correlation. (P)

Aug 2011

A Statistical New World

Some excellent grad school friends of mine created this fun musical take (based on Disney's "A Whole New World") on what it's like to be a statistician---and asked me to perform and handle music production! From the 2011 American Statistical Association "Promoting the Practice and Profession of Statistics" Video Competition.


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