Computing has always been an essential ingredient of statistical practice. While probability theory provides us with a mathematical foundation for describing estimation methodologies and studying statistical inference, computing technologies act as a medium through which analyses are actually realized. Our ability to manipulate data and to audition new methodologies depends on and is limited by our familiarity with computing technologies. To some extent, even our notion of what constitutes "data" is a product of our background in computing.

Through a series of projects, we will study tools for "exploratory computing." We will emphasize programming and scripting languages over point-and-click interfaces. We hope to instill a problem solving ability so that you will learn languages on your own, cull online documentation or tutorials, find books and manuals.

Computing Resources

This year, we have been awarded an Amazon Web Services educational grant and most of our computations will be performed on their Elastic Compute Cloud service. This approach will provide us with a degree of uniformity in setup and (more importantly) will allow us to audition tools for large-scale data analysis.

Instructor    Mark Hansen
8951 Mathematical Sciences Building
University of California, Los Angeles

Meeting    Monday/Wednesday 3:00-4:20
9413 Boelter

Office Hours    Thursdays 2-3 and Fridays 10-11
(or by appointment)
8951 Mathematical Sciences

Lectures    A listing of the lectures covering
UNIX basics through advanced R.