Course - Probability Theory and Asymptotic Techniques - MA8704
MA8704 - Probability Theory and Asymptotic Techniques
About
Examination arrangement
Examination arrangement: Oral examination
Grade: Passed / Not Passed
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| Oral examination | 100/100 | E |
Course content
The course gives a broad introduction to classical probability theory and asymptotic techniques towards applications in statistics. Together with course MA8701 General statistical methods it provides a theoretical basis for PhD students in statistics. The contents include basic probability theory, convergence of sequences of random variables, characteristic functions, classical limit theorems, asymptotic properties of statistical methods.
Learning outcome
1. Knowledge The course gives a broad introduction to classical probability theory and asymptotic techniques towards applications in statistics. Together with course MA8701 General statistical methods it provides a theoretical basis for PhD students in statistics. The contents include basic probability theory, convergence of sequences of random variables, characteristic functions, classical limit theorems, asymptotic properties of statistical methods. 2. Skills The students should learn and be able to use the basic methods of probability theory and asymptotic analysis as mentioned above. They should be able to apply these methods to various problems in probability theory and statistical inference, as well as in applied mathematics. 3. Competence The students should be able to participate in scientific discussions and conduct research in probability and in asymptotic analysis at a high international level. They should be able to participate in interdisciplinary projects involving these topics.
Learning methods and activities
Lectures, alternatively guided self-study.
The course is taught only if a sufficient number of students register. If too few students register, then the course is only given as a guided self study.
Recommended previous knowledge
The course requires good statistical background, such as TMA4295 Statistical inference or equivalent.
Course materials
Will be announced at the start of the course.
Version: 1
Credits:
7.5 SP
Study level: Doctoral degree level
Term no.: 1
Teaching semester: AUTUMN 2023
Language of instruction: -
Location: Trondheim
- Statistics
Department with academic responsibility
Department of Mathematical Sciences
Examination
Examination arrangement: Oral examination
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD Oral examination 100/100 E
-
Room Building Number of candidates - Spring ORD Oral examination 100/100 E
-
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"