STAT 8670 - Computational Methods in Statistics
Preface
Thank you
The course is finished, thank you everyone for your participation and attention. Hope you all have learned something from this course. Wish everyone has a good winter break!
Description
Topics included are optimization, numerical integration, bootstrapping, cross-validation and Jackknife, density estimation, smoothing, and use of the statistical computer package of S-plus/R.
Prerequisites
MATH 4752/6752 – Mathematical Statistics II, and the ability to program in a high-level language.
Instructor
Chi-Kuang Yeh, I am an Assistant Professor in the Department of Mathematics and Statistics, Georgia State University.
- Office: Suite 1407, 25 Park Place.
- Email: cyeh@gsu.edu.
Office Hour
14:00–15:00 on Tuesday
13:00 - 14:00 on Friday (online) Link Provided on iCollege
Grade Distribution
- Assignments: 40%
- Exam 1: 15%
- Exam 2: 15%
- Project: 30%
Assignment
Midterm
Project
Topics and Corresponding Lectures
Those chapters are based on the lecture notes. This part will be updated frequently.
| Status | Topic | Lecture Covered |
|---|---|---|
| ✅ | R Programming | 1–2 |
| ✅ | Numerical Approaches and Optimization in 1-D | 3–5 |
| ✅ | Review for Distribution | 6–7 |
| ✅ | Random Variable Generation | 8–10 |
| ✅ | Monte Carlo and Integration | 11–15 |
| ✅ | Exam 1 | 13 |
| ✅ | Cross-Validation | 16-17 |
| ✅ | Bootstrap and Jackknife | 18–21 |
| ✅ | Exam 2 | 23 |
| ✅ | Smoothing | 24 |
| ✅ | Density estimation | 25 |
| ✅ | Presentation | 26-28 |
Recommended Textbooks
Givens, G.H. and Hoeting, J.A. (2012). Computational Statistics. Wiley, New York.
Rizzo, M.L. (2007) Statistical Computing with R. CRC Press, Roca Baton.
Hothorn, T. and Everitt, B.S. (2006). A Handbook of Statistical Analyses Using R. CRC Press, Boca Raton.
Side Readings
- Wickham, H., Çetinkaya-Rundel, M. and Grolemund, G. (2023). R for Data Science. O’Reilly.