Course - General Statistical Methods - MA8701
General Statistical Methods
About
About the course
Course content
The course is usually given every second year, and only if a sufficient number of students register. It is given next time Spring 2011. If too few students register, the course is given as a guided self study.
The course gives a broad introduction to the basic principles of statistical inference. Together with course MA8704 (MA8700) Probability theory and asymptotic techniques it provides a theoretical basis for PhD students in statistics.
The course includes:
Thorough and basic introduction to classical statistics: sufficient statistics, exponential families, estimation, hypothesis testing, linear models. Bayesian statistics. Decision theory. Robustness. Non-parametric estimation of distribution functions and density functions. Advanced Bayes-analyses (empirical and non-parametric Bayes methods).
Learning methods and activities
Lectures, alternatively guided self-study.
Recommended previous knowledge
The course builds on TMA4295 Statistical inference, or equivalent knowledge.
Course materials
Peter J. Bickel and Kjell A. Doksum. Mathematical statistics: basic ideas and selected topics, 2nd edition, 2001. Prentice Hall.
Subject areas
- Statistics
Contact information
Course coordinator
- Nikolai Ushakov