Course - Statistical Inference - TMA4295
Statistical Inference
About
About the course
Course content
General principles for statistical analysis. Bayesian,
maximum-likelihood, method of moment and least-squares methods for estimation. Optimal estimators. General theory for confidence intervals and testing of hypothesis. Optimal tests. Asymptotic properties of estimators and tests.
Learning outcome
The course will give a theoretical introduction to general methods for statistical inference.
Learning methods and activities
Lectures and exercises. The lectures may be given in English. Written final examination is the basis for the grade awarded in the course. Retake of examination may be given as an oral examination.
Recommended previous knowledge
The course is based on TMA4240/4245 Statistics or equivalent. The course demands some degree of maturity in Statistics and we also recommend to have TMA4267 Linear Statistical Models or TMA4255 Applied Statistics.
Course materials
George Casella, Roger L. Berger: Statistical inference, 2nd Edition, Duxbury, 2002.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| SIF5084 | 7.5 sp | |
| ST2201 | 7.5 sp |
Subject areas
- Statistics
- Technological subjects
Contact information
Course coordinator
- Nikolai Ushakov