|Prof:||Robert L. Wolpertfirstname.lastname@example.org (211c Old Chem, 684-3275)|
|TA:||Enrique ter Horst Gomezemail@example.com (223a Old Chem, 684-4558)|
|Class:||Mon & Wed 3:55-5:10pm||Soc/Psych 126|
|OH:||Tue 3:00-4:00pm||Old Chemistry 211c|
|Text:||Peter Bickel & Kjell Doksum,||Mathematical Statistics: Basic Ideas and Selected Topics (2nd edn)|
|Opt'l:||James Berger & Robert Wolpert,||The Likelihood Principle (2nd edn)|
|Andrew Gelman, John Carlin,
Hal Stern, & Don Rubin,
|Bayesian Data Analysis|
|John Kalbfleisch & Ross Prentice,||The Statistical Analysis of Failure Time Data|
|Erich Lehmann,||Theory of Point Estimation and Testing Statistical Hypotheses|
Students are assumed to be familiar with random variables and their distributions from a calculus-based or (better) measure-theoretic introduction to probability theory. Some problems and projects will require computation; students should be or become familiar with either S-Plus (some notes and an intro are available, also in an older but nice form (Contents, 1-29, 30-64, 65-85, Examples)) or Matlab (a primer and intro are available), both easier to use than compiled languages like Fortran or C.
Not all homework sets will be graded, but they should be turned in for comment; Monday classes will begin with a class solution of two of the preceeding week's problems. Here is at least a tentative schedule, containing most of the topics below.
OUTLINE -- course topics will include: (look here for a tentative schedule)