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Sentrana Presents Leading-Edge Scientific Research at Joint Statistical Meetings
Sentrana presents scientific research at the largest gathering of statisticians held in North America.
The Joint Statistical Meetings (JSM) is the largest gathering of statisticians held in North America. These meetings provide an opportunity for more than 5000 leading scientists, researchers, and interested individuals to come together for a comprehensive program that address the application of statistics to various real-world problems.
At the 2011 JSM in Miami, Florida, Sentrana Board Member and Carnegie Mellon faculty member Alan Montgomery presented his research in his talk “Web Browsing Using Clickstream Data” regarding the website browsing habits of users. This research explores the sequences that drive website browsing when researching a specific topic. For example, a user may have a session that is focused on gathering information about a product, which may have a large number of viewings at promotional, corporate, and portal sites, while news gathering may have a very different profile. “The idea is that consumers group their activities together into related topics. The goal of this study is to detect the underlying topics that are driving user browsing behavior using a correlated topic model,” says Dr. Montgomery.
Sentrana’s Liuxia Wang presented a paper developed with biostatistician Yulin Li of K&L Consulting. The paper, titled “Order Detection for Factor Analysis Models Using Adaptive Group LASSO,” illustrates a new method that is able to identify the true number of factors needed to summarize more extensive original data. Factor analysis is a statistical test that explores which variables in a data set are most related to each other. From a large data set, a smaller set of variables is defined that essentially summarizes the results of the larger data set. This can have practical benefits when applying statistical methods to analytical models aimed at gaining sharper insight into particular business problems.
“Right now, there are many methods used to define how many variables are needed to summarize the larger data set, but there is still a lack of accuracy when defining the correct number of factors needed. Our new method is shown to outperform some of the current methods,” explains Dr. Wang. In Wang and Li’s method they show through simulated examples that their mathematical approach can more accurately determine the number of factors needed than existing methods. For example, a business in the foodservice industry may want to understand how the price varies over time in the beef market as a whole. Unfortunately this variation is not directly observable. However, the price series for many beef products are observable, and then factor analysis can be used to extract the common price variation patterns that represent the price variation of the entire beef market. Their new method is optimal for addressing these types of problems.
About the Joint Statistical Meetings
The Joint Statistical Meetings are held jointly with the American Statistical Association, the International Biometric Society (ENAR and WNAR), the Institute of Mathematical Statistics, the Statistical Society of Canada, the International Chinese Statistical Association, and the International Indian Statistical Association. Attended by over 5000 people, the meetings include oral presentations, panel sessions, poster presentations, continuing education courses, exhibit hall, career placement service, society and section business meetings, committee meetings, social activities, and networking opportunities.
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