Mathematical Statistics
Mathematical statistics is the application of probability theory to data analysis. It involves collecting, organizing, analyzing, interpreting, and presenting data using rigorous mathematical methods. This course covers the basic principles and techniques of statistical theory for graduate students.
Lecturer
Date
11th October ~ 27th December, 2023
Location
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| Wednesday | 13:30 - 16:55 | A3-3-103 | ZOOM 02 | 518 868 7656 | BIMSA |
Prerequisite
Fundamentals of probability theory and statistics
Syllabus
1.fundamental of probability theory that are used in mathematical statistics;
2.Fundamentals of Statistics;
3.Unbiased Estimation;
4.Estimation in Parametric Models;
5.Hypothesis Tests.
2.Fundamentals of Statistics;
3.Unbiased Estimation;
4.Estimation in Parametric Models;
5.Hypothesis Tests.
Reference
1.Shao, Jun.: Mathematical statistics (Second edition), Springer-Verlag, New York, 2003.
2. 茆诗松、王静龙、濮晓龙: 《高等数理统计(第三版)》,高等教育出版社, 2022.
2. 茆诗松、王静龙、濮晓龙: 《高等数理统计(第三版)》,高等教育出版社, 2022.
Audience
Advanced Undergraduate
, Graduate
Video Public
Yes
Notes Public
Yes
Lecturer Intro
Sixu Liu received her Ph.D. degree from Peking University in 2019. She then worked as a postdoc at Tsinghua University before joining BIMSA as an assistant professor in 2022. Her main research interests include dynamical systems and ergodic theory, as well as statistical experimental design.