Syllabus:
Stat 514, Sp 2005
TA: Joan (Fengjuan) Xuan, 331B Thomas Bld, fxuan@stat.psu.edu, Office Hours: TR 2:00-3:00
Required text: Introduction to Mathematical Statistics, 6th ed, by Hogg, McKean, Craig (HMC)
I plan to cover topics from Chapters 4-8 and Chapter 11. Topics covered include estimation, maximum likelihood estimation and likelihood ratio tests, sufficiency and completeness, optimality, and Bayesian methods. Examples will include regression and analysis of variance.
Homework: Homework will be assigned on a regular basis and is due the class period after it was assigned. It will be graded. Solutions will be posted on the class webpage.
Grading:
The exam will be worth 100 points, and the final will be worth 200 points. The
homework will only be used in case you are on the border between two grades.
(The borders can be large, however.)
Academic integrity: The academic integrity policy of the Eberly College of Science will apply to this course. See www.science.psu.edu/Integrity/index.html
Goals: We will continue to consider model building in Stat 514. The models will involve unknown parameters and the emphasis will be on estimation and testing hypotheses concerning these parameters. In addition, we will spend some time developing asymptotic methods, culminating in the central limit theorem. We will consider inference in standard linear models (regression and designed experiments) and also in some other important models such as mixture models. Throughout, it will be important to determine the sampling distribution (at least approximately) of the statistic we are considering. To that end we use analytical methods (mathematics) and computational methods (bootstrap, simulations, em algorithms). I expect you to be able to develop your own programs in Minitab, S-plus, R, or whatever you are familiar with.