| Course ID: | STAT 8330. 3 hours. |
| Course Title: | Advanced Statistical Applications and Computing |
Course
Description: | Advanced programming and implementation of modern statistical
techniques using statistical software such as R. Topics include
Monte Carlo simulations, resampling techniques, penalized
regression, generalized linear models, robust methods, nonlinear
regression, multiple testing adjustment, and smoothing
techniques. |
| Oasis Title: | Adv Stat App and Comp |
| Prerequisite: | [(STAT 6420 and (STAT 4360/6360 or STAT 4360E/6360E)] or permission of department |
Semester Course
Offered: | Offered fall semester every year. |
| Grading System: | A-F (Traditional) |
|
| Course Objectives: | The goal of this course is to provide students with a survey
of several topics in modern applied statistics with an
emphasis on implementation in a statistical programming
environment. Students will learn how to write their own
functions and code for complex tasks as well as the proper use
of existing functions. There will be lectures on the
statistical methodology associated with each topic followed by
examples involving real data and practical implementation in
statistical software. |
| Topical Outline: | Monte Carlo simulations
Resampling techniques (bootstrap, permutation test, and cross
validation)
Penalized regression
Generalized linear models
Robust methods
Nonlinear regression
Multiple testing adjustment
Smoothing techniques (kernels and splines) |