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
9:00 - 12:00 on Wednesday or by appointment
Grade Distribution
- Assignments: 40%
- Exam: 30%
- Project: 30%
- Attendance: *7%
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– |
| ⏳ | Numerical Approaches and Optimization | TBA |
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.