STAT 662a: Statistical Computing

Jay Emerson

Brief Course Description, 2008:

Topics in the practice of data analysis and statistical computing, with particular attention to problems involving massive data sets or large, complex simulations and computations. Emphasis will be placed on implementation rather than the theoretical framework, focusing on the "programming" side of the R statistical programming environment, C/C++, and Perl. Students will work to improve existing methods as well as implement new parallel algorithms, improving speed and reducing memory requirements wherever possible.

This course is intended primarily for graduate students in statistics; others are welcome, but must seek permission at the start of the semester. Students must have prior experience using R, or significant experience with other scripting or programming languages (such as C/C++, Matlab, Perl, Python, Visual Basic, etcÂ…); prior coursework in data analysis (preferably using R) is required.

Students: please visit the new classes site for this course. Log in with your netid, and then "join" the class!

Department of Statistics

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