Public profile
Research areas
Bayesian methodology, topological and geometrical data analysis, high-dimensional probability
Statistics
Dobelman Family Assistant Professor of Statistics
Member, Ken Kennedy Institute
Average rating
4.0
12 temporary mock ratings
Difficulty
3.9
course-linked average
Courses
3
in seeded sections
Bayesian methodology, topological and geometrical data analysis, high-dimensional probability
STAT 410
An introduction to linear regression and its applications. Topics include simple and multiple linear regression, least squares, analysis of variance, model selection, diagnostics, remedial measures. Applications to real data using statistical software are emphasized. Recommended Prerequisite(s): CMOR 302 or MATH 355. Mutually Exclusive: Cannot register for STAT 410 if student has credit for STAT 615.
STAT 590
Research course for graduate level research in probability and statistics. This course provides 1-15 hours of credit for students who wish to pursue a statistical research project of mutual interest to the student and a faculty member. The student will conduct independent research under the faculty member’s direction. Repeatable for Credit. Repeatable for Credit.
STAT 800
Thesis for Graduate Students. Repeatable for credit. Repeatable for Credit.