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A new SPES and Q&P webinar is coming up on Friday, March 29, 2013 from 3:00-5:00 pm Eastern Time: Join presenters Roger Hoerl from Union College, Richard De Veaux from Williams College, and Ron Snee from Snee Associates who will be co-presenting Effective Data Mining: Applying Statistical Engineering to “Big Data”. The following is a snippet from the webinar description: After an introduction of the Big Data problem, and some discussion of the newer tools now available to analysts, we will discuss the problems that can arise when these statistical engineering fundamentals are ignored, even with well-designed and powerful analytic tools. Further, we will share our thoughts on how to improve data mining projects by incorporating these principles into the overall project. Combining the powerful analytic techniques now available with sound modeling principles and massive data that have a quality “pedigree” can produce groundbreaking results. However, Big Data projects must be built upon a sound statistical engineering foundation, and not upon the sandy foundation of hype and unstated assumptions
The dinner and the Chapter meeting will be in the BEST Conference room after the conclusion of the Chapter’s Traveling Course Successful Data Mining in Practice (see below)
10-17-2013 | 18:00 - 20:30 CT
Spring 2003 Speaker: Dick DeVeaux, Williams College Title of Presentation: "Successful Data Mining in Practice: Where Do We Start?"
03-26-2003
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Heavy mining of satellite, radar, audio messages, sensor, and other Big Data may one day solve the tragic mystery of Malaysian Flight MH370, but the many pure speculations, conspiracy theories, accusations of wrongdoing, and irresponsible lies quoting these data have mercilessly added anguish and misery to the families of the passengers and the crew. No one seems to be tracking the velocity, volume and variety of the false positives that have been generated for this event, or other data mining efforts with Big Data. The responsibility is of course not on the data; it is on the people. There is the old saying that “figures don’t lie, but liars figure.” Big Data – in terms of advancing technology and availability of some massive amount of randomly and non-randomly collected electronic data - will undoubtedly expand the study of statistics and bring our understanding and governance to new heights
– 3:00 pm Clinical Research Building 6th Floor, Room 692 1120 NW 14th Street Miami, Florida RSVP: MICHELE GOMEZ mgomez6@biostat.med.miami.edu Mining for Rules in Data: Modeling Imperfect Implication Rules Rule mining involves the extraction of rules of the type “if A then B” from data. Rules extracted from a finite set of (potentially imperfect) data can hardly be considered perfect
02-14-2013 | 14:00 - 15:00 ET
On Wednesday, October 1, in conjunction with the Fall Technical Conference, SPES will be sponsoring a short course by Heath Rushing entitled "Text mining and unstructured data analysis methods"
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