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To some media’s credit, there are now fact-checkers who regularly examine stories or statements, most of them based on numbers, and evaluate their degree of truthfulness. In the era of Big Data, lies occur in higher velocity with bigger volume and greater variety
Title: An Introduction to the pbdR Project by Ryan Elmore Abstract: In this talk I will give a brief introduction to the pbdR (Programming with Big Data in R) project
09-24-2013 | 19:00 - 20:30 MT
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11-11-2015 | 18:30 - 21:30 PT Irvine, California
[4/13/14: NB, see Big Data Sessions at 2014 Joint Statistical Meetings . 6/22/15: see Big Data Sessions at the 2015 Joint Statistical Meetings ] As I was going through the JSM 2013 Program Book , I noticed many Big Data sessions and thought it would be useful to list them out, which I do below
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In commemoration of Big Data Week April 22-28, I'm sharing a short draft document I'm working on regarding the role of statistics in big data. Clearly, progress from and in big data will be advanced by many scientific disciplines ranging from data mining and computational science to statistics and machine learning. As American Statistical Association (ASA) Executive Director Ron Wasserstein and I wrote in a joint March 2012 blog entry, Big Data and the Role of Statistics , the scientific discipline of statistics can sometimes be left out of the big data discussions
1 Comment - Defining Big Data separately and exactly is not necessary. It is part of statistics; tomorrow’s data will be bigger, more complex, and faster in collection than today’s data. The main challenge is to analyze and understand data that are not collected according to a probability framework. Non-random data have varying degree of inherent value and should no longer be simply ignored or dismissed
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[8/19/14 update: Applications for 2015-2016 Executive, Congressional and Judicial Branch Fellowships are due November 1: https://fellowshipapp.aaas.org/applications/default.asp . To see the 2014-15 Big Data and Analytics Fellows, click here .]
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