I'm headed out to PyCon 2019! This year, I will be co-instructing two tutorials, one on network analysis and one on Bayesian statistics, and delivering one talk on Bayesian statistics.
The first tutorial on network analysis is based on material that I first developed 5 years ago, and have continually updated. I've enjoyed teaching this tutorial because it represents a different way of thinking about data - in other words, relationally. This year, I will be a co-instructor for Mridul, who has kindly agreed to step up and teach it this year at PyCon. The apprentice has exceeded the master!
The second tutorial on Bayesian statistics is based on material co-developed with Hugo Bowne-Anderson. Hugo is a mathematician by training, a pedagogy master, and data science aficionado. Like myself, he is a fan of Bayesian statistical modelling methods, and we first debuted the tutorial past year at SciPy. We're super excited for this one!
The talk that I will deliver is on Bayesian statistical analysis of case/control tests. In particular, I noticed a content gap in the data science talks, where case/control comparisons were limited to one case and one control. One epiphany I came to was that if we use Bayesian methods to analyze our data, there's no particular reason to limit ourselves to one case and one control; we can flexibly model multiple cases vs. one control, or even multiple cases vs multiple different controls in the same analysis, in a fashion that is flexible and principled.
My final involvement with PyCon this year is as Financial Aid Chair. This is the first year that I'm leading the FinAid effort; during previous years, I had learned a ton from the previous chair Karan Goel. My co-chairs this year are Denise Williams and Jigyasa Grover; I'm looking forward to meeting them in 3D!
All-in-all, I'm looking forward to another fun year at PyCon!