2012 UCLA DataFest: Friday, May 4 |
The second annual 2012 UCLA DataFest will take place Friday, May 4 through Sunday, May 6. Watch teams of undergraduate students work around-the-clock to explore a complex and rich dataset and to mine it for insight and understanding. Each team will have just 10 minutes and two slides to convince the judges to award them valuable prizes. Prizes will go to teams with the best visualization, the best use of external data, and the best insight. Students who wish to participate should visit http://datafest.stat.ucla.edu for instructions. Visitors are quite welcome to drop by for an hour or more and assist the teams Please email Rob Gould at rgould@stat.ucla.edu. The event begins promptly at 6pm on Friday, May 4 at the IPAM building. |
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Robert Gould: ASA Fellow |
The American Statistical Association Committee on Fellows has selected Rob Gould as a 2012 Fellow for his outstanding contributions to the statistical profession. Fellows will be presented with their awards on Tuesday, July 31, 2012, at 8:00 p.m. in San Diego, California at the San Diego Convention Center during the Joint Statistical Meetings awards ceremony. We congratulate Rob Gould on his achievement. |
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Coding for a Cause |
Congratulations to Maria Pavlovskaia and the rest of her team for winning UCLA's fifth annual Coding for a Cause Competition in January. In this competition teams of up to five people pick a project to improve the lives of the disabled. Maria's team chose to create an online Sudoku application for blind and visually impaired people. Sudoku is a numerical puzzle whose objective is to fill a partially completed 9x9 grid with digits so that each column, each row, and each of the nine 3x3 sub-grids that compose the grid contain all of the digits from 1 to 9. The application they created had the ability to: read out sections of the grid and answer common questions about the status of the grid. It had a large easy-to-read uncluttered display for the visually impaired and text output with screen reader capability for the blind. This two-day event was sponsored by Project: Possibility, a nonprofit organization dedicated to creating open source software for persons with disabilities. The four other members of Maria's team were: Kyle Morton, Roger Call, Inchara Shivalingaiah and Damon Alexander. The team went on in March to compete at the 27th Annual International Technology and Persons with Disabilities Conference at CSUN. They placed third. |
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Project Cascade Among Fast Company's 22 Best Infographics for 2011 |
 Infographics can help struggling news organizations exploit the nuances of social media to reach more readers. Here, data-viz wiz Jer Thorp, UCLA prof Mark Hansen, and staff data scientist Jake Porway developed a way for the New York Times to visualize how stories spread across Twitter--info the paper can then use to program tweets that grow their audience (and, hopefully, their ad dollars). Find out more about the Cascade project at |
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Teaching Computers To See |
 Statistics professor Song-Chu Zhu studies artificial intelligence to help computers understand one of the most challenging skills of all. Read more about Song-Chun's work in this UCLA College Report... |
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Journal of Statistical Software Ranked Among "Rising Stars" Among Journals Two Years in a Row |
Thomson-Reuters, who also have the Journal of Statistical Software listed in computer science, have (for the second time) crowned the journal a "Rising Star", which means it is the fastest growing journal in computer science (in terms of their impact statistics). It would be nice if the journal could be listed in Statistics, but both Elsevier and Thomson are not really aware of the fact that Statistics exists (except as a branch of Mathematics). |
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Jan de Leeuw on "History and Theory of Nonlinear Principal Component Analysis" |
A talk was given by Jan de Leeuw, Feb 11 on the occasion of the CARME 2011 organized by the Applied Mathematic Department Agrocampus Ouest. Title: History and Theory of Nonlinear Principal Component Analysis Abstract: Multiple Correspondence Analysis (MCA) is discussed as a form of Nonlinear Principal Component Analysis (NLPCA). It is compared with other forms of NLPCA that have been proposed over the years: Shepard-Kruskal-Breiman-Friedman-Gi PCA with optimal scaling, aspect analysis of correlations, Guttman's MSA, Logit/Probit PCA of binary data, and Logistic Homogeneity Analysis. Watch the presentation on YouTube at http://www.youtube.com/watch?v=V-hFORcBj44 |
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Why Statistics?
The world is becoming more and more quantitative. Many professions depend on numerical measurements to make decisions
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