STAT 442T(S) Computational Statistics and Data Mining (Q)
In both science and industry today, the ability to collect and store data can outpace our ability to analyze it. Traditional techniques in statistics are often unable to cope with the size and complexity of today's data bases and data warehouses. New methodologies in Statistics have recently been developed, designed to address these inadequacies, emphasizing visualization, exploration and empirical model building at the expense of traditional hypothesis testing. In this course we will examine these new techniques and apply them to a variety of real data sets using Silicon Graphics workstations.
Evaluation will be based primarily on homeworks and projects.
Prerequisites: Statistics 346 or permission of instructor. Enrollment limit: 10. (expected:10).
Tutorial meetings to be arranged. R. DEVEAUX