TILM3519 Theory of Statistical Inference (6 cr)
Cooperation network course
Network: Cross-institutional studies in advanced courses in mathematics and statistics
This course is offered through the Network for Advanced Studies in Mathematics. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Master's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master's Degree Programme in Mathematics (Subject Teacher)
- Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Doctoral Programme in Mathematics and Statistics
- Doctoral Programme in Mathematics and Science (Specialication in Mathematics)
Grading scale:
0-5
Description
Sufficient statistics and factorization criterion. Fisher information, score function and information inequality. Delta method. Consistency and asymptotic normality of maximum likelihood estimators. Asymptotic tests.
Learning outcomes
The student acquires knowledge of some basic principles of statitical inference and their theoretical foundations. In particular, the student is able to investigate and describe the asymptotic behaviour of maximum likelihood estimators in large samples, and utilize these results in hypothesis testing and creation of confidence intervals.
Additional information
Opintojakso on tarjolla joka toinen vuosi ja seuraavan kerran se tarjotaan syksyllä 2026.
Description of prerequisites
Statistical Inference I and II, and their prerequisites.