School of Public Health
(3.0 cr; prereq [[7450, 8432, Stat 5102], Stat 8112 preferred, advanced [biostatistics or statistics] major] or #) The course develops statistical methods for the design and analysis of sequential experiments. Underlying theory includes Wald theorems, stopping times, martingales, Brownian motion, dynamic programming. Bayesian and frequentist approaches are compared and contrasted. Applications to interim monitoring of clinical trials are emphasized. Effective: Fall 2008
Professor: Patricia Grambsch, Ph.D.
gramb001@umn.edu.
612-624-0418
A-466, Mayo Building, Division of Biostatistics
Class Times
TTh 2:30p.m.-3:45p.m.
Classroom
Tues.: MoosT 2-580 Thurs: Weaver-Densford 2120
Web address of this page: My Home Page
Most recent update: Aug. 11, 2006