Distribution-free inference, game and decision theory, advanced theory of estimation (including sequential estimation), robustness, advanced probability theory, stochastic processes or empirical processes. Prerequisite: permission of instructor. Offered: Sp.
This is a case-based course, meaning that we will work in groups on a few scientific problems. The groups will be selected by the instructor to ensure that each group has a variety of different expertise. Background material will be available on the web. Each case will take about 2-3 weeks. Different cases will be presented to the class by the groups in different ways, such as papers, oral presentations, posters, or web pages.
The course is available both for graduate and undergraduate students. The main requirement is a course in regression, such as STAT 421 or STAT 504 and some elementary probability. Familiarity with R is helpful.
Possible cases include: Estimating daily mean temperature from observations Detecting trends in minimum daily temperature or in precipitation Sea level rise Uncertainty in rankings (such as "2013 is the second warmest year on record worldwide")
Student learning goals
General method of instruction
Understanding of regression and elementary probability.
Class assignments and grading