You are invited to come to our next seminar...
Data Science: Will Computer Science and Informatics Eat Our Lunch?
Professor Thomas Lumley
Department of Statistics, University of Auckland
Tuesday 1st September 2015
5:45pm – Light refreshments in the Staff Tea Room, Richard Berry Building, The University of Melbourne.
6:15pm – Theatre 1, Old Geology, The University of Melbourne.
7:30pm – Dinner with our speaker at Café Italia.
About the speaker
Thomas Lumley is Professor of Biostatistics at the University of Auckland. He studied mathematics at Monash, applied statistics at Oxford, and biostatistics at the University of Washington. Thomas spent twelve years on the staff of the Biostatistics department at the University of Washington before moving to Auckland in 2010. His main applied research is in cardiovascular epidemiology and genomics, and his main statistical research is in analysis of complex samples and related issues in semiparametrics. He is a member of the R Core Development Team, and a Fellow of the American Statistical Association.
Mainstream statistics ignored computing for many years, so that students were taught to handle infinite N, but not N of a million. Practical estimation of conditional probabilities and conditional distributions in large data sets was often left to computer science and informatics. Although statistics started behind, we are catching up: many individual statisticians and some statistics departments are taking computing seriously. More importantly, applied statistics has a long tradition of understanding how to formulate questions: large-scale empirical data can tell you a lot of things, but not what your question is. Big Data are not only Big but Complex, Messy, Badly Sampled, and Creepy. These are problems that statistics has thought about for some time, so we have the opportunity to take all the shiny computing technology that other people have developed and use it to re-establish statistics in data science.
You are invited to join us for dinner at Café Italia after the meeting. Free car parking is not available on campus. There is easy access by public transport. Information about car parking at the University can be found at: http://www.pcs.unimelb.edu.au/services/parking/car_parks (https://async.racgp.org.au/owa/redir.aspx?C=eG54KD1HMEqPOrBpz3V0oad8IspOcdIILMp9rWol1CQFWX550u_p389x_gHdEXn7iuNZEvC0XqM.&URL=http%3a%2f%2fwww.pcs.unimelb.edu.au%2fservices%2fparking%2fcar_parks)
A map of the Parkville campus can be found at: http://www.pcs.unimelb.edu.au/maps_and_locations/campus_maps.html (https://async.racgp.org.au/owa/redir.aspx?C=eG54KD1HMEqPOrBpz3V0oad8IspOcdIILMp9rWol1CQFWX550u_p389x_gHdEXn7iuNZEvC0XqM.&URL=http%3a%2f%2fwww.pcs.unimelb.edu.au%2fmaps_and_locations%2fcampus_maps.html)
Stay connected Like us on Facebook (https://www.facebook.com/pages/Statistical-Society-of-Australia-Victorian-Branch/272824249396943?fref=ts), add us on LinkedIn (http://www.linkedin.com/groups?home=&gid=5085191&trk=anet_ug_hm) and visit our website today.