| Detailed information |
| Original study plan |
Master's programme Mathematics for Natural Sciences (discontinuing at 28/2/2026) 2022W |
| Objectives |
At the end of the course, students will have a theoretical understanding of the main concepts and fundamental methods for statistical inference.
|
| Subject |
Statistical models, statistics and related theorems, point estimators, interval estimators, hypothesis testing, statistical inference for stochastic processes.
|
| Criteria for evaluation |
Oral exam
|
| Methods |
Blackboard presentation, supported by lecture slides.
|
| Language |
English and French |
| Study material |
- Statistical Inference, G. Casella and R. L. Berger
- Introduction to the theory of Statistical Inference, H. Liero and S. Zwanzig
- Introductory Statistics, S. M. Ross
- Introduction to Probability and Statistics for Engineers and Scientists, S. M. Ross.
|
| Changing subject? |
No |
| Further information |
Until term 2022S known as: TMAPBVOSTAT VL Statistical methods
|
| Earlier variants |
They also cover the requirements of the curriculum (from - to)
TMAPBVOSTAT: VO Statistical methods (2003W-2022S)
|
