Data R Us

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Ever wondered how programmers actually deal with all the information they get with “big data?” The answer is a programming language called R. R is an open source programming language and software environment for statistical computing and graphics. It is a popular tool for statistical analysis tasks and working with “big data.”

The Princeton chapter of the ACM/IEEE will hold a free meeting Thursday, April 20, at 8 p.m. at the Princeton University Computer Science building, Room 105, where Richard Heiberger, a professor of statistics at Temple, will discuss how the unique programming language is used. For more information, visit www.princtonacm.acm.org or call 908-285-1066.

Graphs are often the output of data analysis because graphs provide the best means of communication between the data analyst and the client. The principles of good graphs and why they are important will be discussed. This talk is based on work in R done by Heiberger over the past 30 years. He began work on the language during a sabbatical he took to work at Bell Labs. The talk will show the analysis philosophy at Bell Labs at the time the language was designed, discuss how that philosophy is reflected in the structure of the language, and explain the software interface to the analysis and graphical procedures in the language.

Heiberger is professor emeritus of statistics in the Fox School at Temple University. His primary research area is statistical computing, with emphasis on linear models, statistical graphics, and software design. He teaches graduate courses in statistical methodology, statistical computing, and design of experiments, and supervises doctoral dissertations in statistics.

Heiberger received his bachelor’s from Oberlin College and a doctorate in statistics from Harvard. He is an elected fellow of the American Statistical Association and was the 2011 chair of the ASA section on statistical computing. He has co-written the graduate-level textbook “Statistical Analysis and Data Display: An Intermediate Course with Examples in R, second edition.”

CE – US1

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