Statistics 526

Advanced Statistical Methodology

Spring 2017

Instructor: Chong Gu
Classes: 1:30 - 2:20 MWF, REC 114
Office Hours: 2:30 - 3:30 MWF, HAAS 170, or by appointment


The final will be on Monday, May 1, 1-3pm, in REC 114. You can bring 4 letter-size, double-sided crib sheets, and a calculator; no mobile devices. Here is an old final.

Course outline
As a sequel to STAT 525, this course introduces some statistical modeling tools that are developed for situations where least squares regression and standard ANOVA techniques may not naturally apply. Our coverage centers around two lines of models that are closely related, the generalized linear models (GLM) for regression (and ANOVA) with non Gaussian responses, and survival models for the analysis of lifetime data. Among issues to be discussed are the estimation of the models, the testing of hypotheses, and the checking of model adequacy. Data examples will be used throughout the course to illustrate the methodologies and the related software tools.

Prerequisite
Working knowledge of basic statistical inference and modeling, such as the maximum likelihood estimate, the likelihood ratio test, and the standard linear models.

Textbook

References

Software
We will be using R, an open-source environment not unlike S/Splus, as the primary platform for computation and graphics. R resources are to be found at CRAN, the Comprehensive R Archive Network.

The following tutorial document should be helpful to you, especially if you had little previous exposure to R/S/Splus.
Course Work
There will be biweekly homework assignments, a midterm, and a final. The assignments will contribute about 40% to the course grade, the midterm 30%, and the final 30%. You are encouraged to discuss with each other on the homework assignments, but you are expected to do your independent work.

Lecture Notes

Homework Assignments