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 1 | The Simply Statistics Unconference on the Future of Statistics 
 2 | ====================================
 3 | 
 4 | Simply Statistics http://simplystatistics.org/ held an unconference on the future of statistics that was 
 5 | live streamed on Youtube October 30th, 2013 12pm-1pm EDT. The conference featured some of 
 6 | the brightest young minds discussing their views on where our discipline is going and had a 
 7 | 24 hour viewership of over 3,000. You can watch the whole unconference at http://bit.ly/198GoL3 or 
 8 | follow the real-time discussion on Twitter by searching the hashtag: [#futureofstats](https://twitter.com/search?q=%23futureofstats&src=hash&f=realtime). Below is a 
 9 | brief summary of each speaker’s points compiled by the Simply Statistics Bloggers Jeff Leek, Roger Peng, 
10 | and Rafa Irizarry.
11 | 
12 | ### The Future of Statistical Software by Hadley Wickham 
13 | * The future of statistical software development will be on Github.
14 | * We will move from static (PDF, LaTeX) to Web (R markdown, HTML) statistical documents.
15 | * It is important to balance ease of use (R) and computational speed (Julia, C++) in statistical software.
16 | 
17 | ### The Future of Statistical Methods by Daniela Witten
18 | * The future of statistical methods is renewed interest in inference.
19 | * We are getting better at prediction; inferential understanding of machine learning is the future.
20 | * We will move from black box machine learning to understanding scientific relationships.
21 | 
22 | ### The Future of Statistical Education by Joe Blitzstein
23 | * The future of statistical education will be more applied and more computational and will involve clear statistical motivations for individual topics
24 | * We will move away from overused data sets to using new and “live” data
25 | * The future in some classes is moving the emphasis from basic calculus computations to deeper understanding.
26 | 
27 | ### The Future of Statistics in Biology by Hongkai Ji
28 | * The future of statistics in biology will be determined by selection pressure of real problems
29 | * There will be two equally important roles of statisticians: as safeguards and engines of discovery
30 | * The future involves reanalysis of large public data sets to create new biological discoveries
31 | 
32 | ### The Future of Statistics in the Social Sciences by Sinan Aral
33 | * The future of statistics in social sciences is designed experiments and causal inference
34 | * The data we will observe will not be i.i.d. - neither are the data we had previously
35 | * We will need sampling strategies that are scalable and deal with n.i.i.d. data; an example is the important issue of interference
36 | 
37 | ### The Future of Statistics and Data Science by Hilary Mason
38 | * The future of statistics will be statistics done by everyone - people with statistics degrees and people without statistics degrees 
39 | * To thrive in industry, statisticians need to augment their stats knowledge with knowledge about software development in teams and how to engineer data products
40 | * 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.
41 | 


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