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San Diego

San Diego, CA – Ben Webster and Katie Bakewell, Lead Statisticians at NLP Logix, will be presenting at the annual American Statistical Conference on Statistical Practice in San Diego, California from Thursday, February 18 to Saturday, February 20.

Ben will be following the “Big Data Prediction and Analytics” track and will be presenting his work titled “Analysis of Survival Functions in Predicting Length of Stay in Florida Hospitals.  His work focused on using a Failure Time Model on a data set acquired from the Florida Agency for Health Care Administration, which contained every inpatient admission and discharge, for every hospital in the state over the course of three years.

“I am pleased the work I did around modeling the primary diagnosis that Medicare has focused upon to apply financial penalties for excessive re-admissions has gained such attention” said Webster.  “We have already had opportunities to apply this work into practical situations for a number of our customers including the Florida Poison Information Center Network/University of Florida.

Katie will be following the “Data Modeling and Analysis” track and will be presenting her work titled “A forecasting Model for Futures Prices Based on Time Series Analysis”.  Katie’s work is a direct result of the work she did for one of the largest dairies in the State of Florida and which caught the eye of UK-based Tesco, which sponsored Joe Towers, a Tesco Scholar, to travel to the Jacksonville and study implementing “Big Data” in the dairy supply chain.

“Having the opportunity to see my work be recognized on the international stage is a great honor” said Bakewell.  “And to have it lead to a Tesco Scholar who runs a dairy farm very close to where I was born shows how small the world really is.”

In addition to attending the conference, Ben and Katie plan on taking in some of the sights of San Diego and the surrounding area with their travel partner, Dr. Pali Sen, Professor of Statistics, Department of Mathematics and Statistics, University of North Florida.

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