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The Simply Statistics Unconference on the Future of Statistics

Simply Statistics held an unconference on the future of statistics that was live streamed on Youtube October 30th, 2013 12pm-1pm EDT. The conference featured some of the brightest young minds discussing their views on where our discipline is going and had a 24 hour viewership of over 3,000. You can watch the whole unconference at or follow the real-time discussion on Twitter by searching the hashtag: #futureofstats. Below is a brief summary of each speaker’s points compiled by the Simply Statistics Bloggers Jeff Leek, Roger Peng, and Rafa Irizarry.

The Future of Statistical Software by Hadley Wickham

  • The future of statistical software development will be on Github.
  • We will move from static (PDF, LaTeX) to Web (R markdown, HTML) statistical documents.
  • It is important to balance ease of use (R) and computational speed (Julia, C++) in statistical software.

The Future of Statistical Methods by Daniela Witten

  • The future of statistical methods is renewed interest in inference.
  • We are getting better at prediction; inferential understanding of machine learning is the future.
  • We will move from black box machine learning to understanding scientific relationships.

The Future of Statistical Education by Joe Blitzstein

  • The future of statistical education will be more applied and more computational and will involve clear statistical motivations for individual topics
  • We will move away from overused data sets to using new and “live” data
  • The future in some classes is moving the emphasis from basic calculus computations to deeper understanding.

The Future of Statistics in Biology by Hongkai Ji

  • The future of statistics in biology will be determined by selection pressure of real problems
  • There will be two equally important roles of statisticians: as safeguards and engines of discovery
  • The future involves reanalysis of large public data sets to create new biological discoveries

The Future of Statistics in the Social Sciences by Sinan Aral

  • The future of statistics in social sciences is designed experiments and causal inference
  • The data we will observe will not be i.i.d. - neither are the data we had previously
  • We will need sampling strategies that are scalable and deal with n.i.i.d. data; an example is the important issue of interference

The Future of Statistics and Data Science by Hilary Mason

  • The future of statistics will be statistics done by everyone - people with statistics degrees and people without statistics degrees
  • To thrive in industry, statisticians need to augment their stats knowledge with knowledge about software development in teams and how to engineer data products
  • You often run into problems you’d like to solve in a year - but you only get a week - statisticians will need to be problem solvers.