spring 2024
STA-3001 Computer-intensive Statistics - 10 ECTS
Course content
The course includes stochastic simulation, bootstrapping, Bayes theory, Laplace methods, the EM algorithm and Markov chain Monte Carlo (MCMC) techniques. The course is lectured in 5 parts. After each part the students must work independently with mandatory homework exercises. These must be approved to take the final exam, and the grades will be a part of the total evaluation.Objectives of the course
The course includes stochastic simulation, bootstrapping, Bayes theory, Laplace methods, the EM algorithm and Bayesian methods like Markov cahin Monte Carlo (MCMC) and Integrated nested Laplace approximations (INLA). After each part the students must work independently with mandatory homework exercises.
The candidate shall:
- obtain a solid knowledge and understanding of stochastic simulation, bootstrapping, Bayes theory, Laplace methods, the EM algorithm, MCMA and INLA techniques.
- be able to apply these concepts to solve theoretical problems.¿
- be able to apply these concepts in independent homework exercises using computers.
Information to incoming exchange students
This course is available for inbound exchange students.
This course is open for inbound exchange student who meets the admission requirements. Please see the Admission requirements.
Do you have questions about this module? Please check the following website to contact the course coordinator for exchange students at the faculty: INBOUND STUDENT MOBILITY: COURSE COORDINATORS AT THE FACULTIES | UiT
Schedule
Examination
Examination: | Date: | Duration: | Grade scale: |
---|---|---|---|
Oral exam | 14.05.2024–15.05.2024 | 30 Minutes | A–E, fail F |
Coursework requirements:To take an examination, the student must have passed the following coursework requirements: |
|||
Coursework | Approved – not approved |
- About the course
- Campus: Tromsø |
- ECTS: 10
- Course code: STA-3001
- Responsible unit
- Matematihka ja statistihka instituhtta
- Earlier years and semesters for this topic