STAT 8670 – Computational Methods in Statistics
2026 Fall Course Notes
Preface
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
Wednesday 9:00 - 12:00 or by appointment
Grade Distribution
- Assignments: 40%
- Exam: 30%
- Project: 30%
- Attendance: *7%
Assignment
Midterm
Project
Start with Instruction for a quick overview and a few topic ideas.
Work in groups of 1-3 students on a statistical method implemented in R or Python. Select from the instructor’s topic list or propose a topic for instructor approval.
Package option: You may submit either an R package or a Python package. Python users should follow the Python package requirements; both languages use the same grading rubric.
Topics and Corresponding Lectures
Those chapters are based on the lecture notes. This part will be updated frequently.
| Status | Chapter | Topic | Lecture |
|---|---|---|---|
| ✅ | Ch. 1 | R Programming | 1–3 |
| ✅ | Ch. 2 | Intro to Computational Statistics | 4–5 |
| ✅ | Ch. 3 | Optimization | 6–10 |
| ⏳ | Ch. 4 | Generating Random Variable | 11– |
| ✅ | Exam 1 | 13 | |
| 📝 | Exam 2 | 24 |
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.