Changzhi Ma
Assistant Professor of Statistical and Data Sciences
Biography
Areas of Interest
My research centers on time series modeling, especially long-memory and spectral methods to reveal persistent structure in real-world data. Much of my work focuses on economic indicators like the Consumer Price Index (CPI), using time-series analysis to study persistent movements that shape how we view inflation and economic stability. I’ve also analyzed healthcare data, including HbA1c levels in diabetes patients, to understand how these measures reflect long-term health outcomes.
I also study organizational behavior data, using quantitative methods to examine employee ethics and behavior. Across economics, healthcare, and management science, my goal is to connect practical problems with clear, data-driven insights.
Courses Taught
- Introduction to Statistics
- Probability Theory
- Statistical Theory
Professional Experience
Selected Talks
- WSDS 2025 – Long-Range Dependence in Economic Time Series: Improved Estimation and Forecasting of CPI Using a Modified GPH Method.
ASA Women in Statistics and Data Science, Cincinnati, OH, Nov. 12-14, 2025. - WSDS 2024 – Estimation of the Long-Range Dependence Parameter in Processes with Stationary Increments.
ASA Women in Statistics and Data Science, Reston, VA, Oct. 16-18, 2024. - JSM 2024 – Estimation of the Long-Range Dependence Parameter in Processes with Stationary Increments.
ASA Joint Statistical Meetings, Portland, OR, Aug. 3-8, 2024. - SDSS 2024 – Estimation of the Long-Range Dependence Parameter with Stationary Increments.
ASA Symposium on Data Science and Statistics, Richmond, VA, June 4-7, 2024.
Want to learn more?
Interested in Statistical Data Sciences or have questions about courses? Feel free to reach out!
Contact Changzhi